Digital.images

8/2/2019 Digital.images

1/17


2/17

Digital Image Basics 1

Written by Jonathan Sachs

Copyright 1996-1999 Digital Light & Color

Digital Image Basics

Introduction

When using digital equipment to capture, store, modify and view photographic

images, they must first be converted to a set of numbers in a process called digitiza-

tion or scanning. Computers are very good at storing and manipulating numbers, so

once your image has been digitized you can use your computer to archive, examine,

alter, display, transmit, or print your photographs in an incredible variety of ways.

Pixels and Bitmaps

Digital images are composed ofpixels (short for picture elements). Each pixel rep-

resents the color (or gray level for black and white photos) at a single point in the

image, so a pixel is like a tiny dot of a particular color. By measuring the color of an

image at a large number of points, we can create a digital approximation of the image

from which a copy of the original can be reconstructed. Pixels are a little like grain

particles in a conventional photographic image, but arranged in a regular pattern of

rows and columns and store information somewhat differently. A digital image is arectangular array of pixels sometimes called a bitmap.


3/17


2 Digital Image Basics

Types of Digital Images

For photographic purposes, there are two important types of digital imagescolor

and black and white. Color images are made up of colored pixels while black and

white images are made of pixels in different shades of gray.

Black and White Images

A black and white image is made up of pixels each of which holds a single number

corresponding to the gray level of the image at a particular location. These gray lev-

els span the full range from black to white in a series of very fine steps, normally

256 different grays. Since the eye can barely distinguish about 200 different gray

levels, this is enough to give the illusion of a stepless tonal scale as illustrated

below:

Assuming 256 gray levels, each black and white pixel can be stored in a single byte

(8 bits) of memory.

Color Images

A color image is made up of pixels each of which holds three numbers correspond-

ing to the red, green, and blue levels of the image at a particular location. Red,

green, and blue (sometimes referred to as RGB) are the primary colors for mixing

lightthese so-called additive primary colors are different from the subtractive pri-

mary colors used for mixing paints (cyan, magenta, and yellow). Any color can be

created by mixing the correct amounts of red, green, and blue light. Assuming 256

levels for each primary, each color pixel can be stored in three bytes (24 bits) of

memory. This corresponds to roughly 16.7 million different possible colors.

Note that for images of the same size, a black and white version will use three times

less memory than a color version.


4/17


Types of Digital Images

Binary or Bilevel Images

Binary images use only a single bit to represent each pixel. Since a bit can only

exist in two stateson or off, every pixel in a binary image must be one of two col-ors, usually black or white. This inability to represent intermediate shades of gray is

what limits their usefulness in dealing with photographic images.

Indexed Color Images

Some color images are created using a limited palette of colors, typically 256 dif-

ferent colors. These images are referred to as indexed color images because the data

for each pixel consists of a palette index indicating which of the colors in the palette

applies to that pixel. There are several problems with using indexed color to repre-

sent photographic images. First, if the image contains more different colors than are

in the palette, techniques such as dithering must be applied to represent the missingcolors and this degrades the image. Second, combining two indexed color images

that use different palettes or even retouching part of a single indexed color image

creates problems because of the limited number of available colors.


5/17



Resolution

The more points at which we sample the image by measuring its color, the more

detail we can capture. The density of pixels in an image is referred to as its resolu-

tion. The higher the resolution, the more information the image contains. If we keep

the image size the same and increase the resolution, the image gets sharper and

more detailed. Alternatively, with a higher resolution image, we can produce a

larger image with the same amount of detail.

For example, the following images illustrate what happens as we reduce the resolu-

tion of an image while keeping its size the samethe pixels get larger and larger

and there is less and less detail in the image:

Original (400x262) Half Size (200x131)

Eighth Size (50x32)Quarter Size (100x65)


6/17


Color Terminology

As we reduce the resolution of an image while keeping its pixels the same sizethe

image gets smaller and smaller while the amount of detail (per square inch) stays the

same:

Color Terminology

While pixels are normally stored within the computer according to their red, green,

and blue levels, this method of specifying colors (sometimes called the RGB color

space) does not correspond to the way we normally perceive and categorize colors.

There are many different ways to specify colors, but the most useful ones work by

separating out the hue, saturation, and brightness components of a color.

Primary and Secondary Colors and Additive and Subtractive Color

Mixing

Primary colors are those that cannot be created by mixing other colors. Because of

the way we perceive colors using three different sets of wavelengths, there are three

primary colors. Any color can be represented as some mixture of these three pri-

mary colors.

There are two different ways to combine colorsadditive and subtractive color

mixing.

Subtractive color mixing is the one most of us learned in school, and it describes

how two colored paints or inks combine on a piece of paper. The three subtractive


7/17



primaries are Cyan (blue-green), Magenta (purple-red), and Yellow (not Blue, Red,

and Yellow as we were taught).

Additive color mixing refers to combining lights of two different colors, for exam-

ple by shining two colored spotlights on the same white wall. The additive colormodel is the one used in computer displays as the image is formed on the face of the

monitor by combining beams of red, green, and blue light in different proportions.

Color printers use the subtractive color model and use cyan, magenta, and yellow

inks. To compensate for the impure nature of most printing inks, a fourth color,

black is also used since the black obtained by combining cyan, magenta, and yellow

inks is often a murky dark green rather than a deep, rich black. For this and other

reasons, commercial color printing presses use a 4-color process to reproduce color

images in magazines.

A color created by mixing equal amounts of two primary colors is called a second-

ary. In the additive color system, the primary colors are:

and the secondary colors are:

In the subtractive color system, the roles of the primaries and secondaries are

reversed.

Color Gamut

In the real world, the ideal of creating any visible color by mixing three primary

colors is never actually achieved. The dyes, pigments, and phosphors used to create

colors on paper or computer screens are imperfect and cannot recreate the full range

of visible colors. The actual range of colors achievable by a particular device or

medium is called its color gamut and this is mostly but not entirely determined by

the characteristics of its primary colors. Since different devices such as computer

monitors, printers, scanners, and photographic film all have different color gamuts,

the problem of achieving consistent color is quite challenging. Different media also

differ in their total dynamic rangehow dark is the darkest achievable black andhow light is the brightest white.

sRed

sGreen

sBlue

sCyan

sMagenta

sYellow


8/17


Color Terminology

Color Management

The process of getting an image to look the same between two or more different

media or devices is called color management, and there are many different color

management systems available today. Unfortunately, most are complex, expensive,and not available for a full range of devices.

Hue

The hue of a color identifies what is commonly called color. For example, all reds

have a similar hue value whether they are light, dark, intense, or pastel.

Saturation

The saturation of a color identifies how pure or intense the color is. A fully satu-

rated color is deep and brilliantas the saturation decreases, the color gets palerand more washed out until it eventually fades to neutral.

Brightness

The brightness of a color identifies how light or dark the color is. Any color whose

brightness is zero is black, regardless of its hue or saturation. There are different

schemes for specifying a color's brightness and depending on which one is used, the

results of lightening a color can vary considerably.

Luminance

The luminance of a color is a measure of its perceived brightness. The computation

of luminance takes into account the fact that the human eye is far more sensitive to

certain colors (like yellow-green) than to others (like blue).

Chrominance

Chrominance is a complementary concept to luminance. If you think of how a tele-

vision signal works, there are two componentsa black and white image which

represents the luminance and a color signal which contains the chrominance infor-

mation. Chrominance is a 2-dimensional color space that represents hue and satura-

tion, independent of brightness.


9/17



Viewing Images on a Monitor

Before you can get consistent results working with digital images, you must create

a standard viewing environment.

Most computer monitors use a standard set ofphosphors (the chemical compounds

on the face of the screen that are responsible for creating its primary colors). These

phosphors, combined with the electronic circuitry that activates them create color

images on your computer screen. To get an accurate match between what you see

on your monitor and prints or other output requires that a number of variables be

controlled:

Viewing Conditions

First, it is very important for critical evaluation of photographic images on a com-

puter monitor to work in an environment with subdued lighting. When strong roomlight falls on the face of the monitor, it makes it almost impossible to discern

shadow detail and seriously alters the appearance of many of the colors.

Monitor Brightness Control

Next, you must set the brightness control on your monitor correctly. If the level is

too high, blacks will start to become grays and colors will be washed out. If the

level is too low, there will be loss of shadow detail and colors will appear murky.

Gamma

Since the human eye has a nonlinear response curve (it is more sensitive to varia-

tions in low light than to an equal variation in bright light), it is important to track

this nonlinearity with the display of different gray levels. The curve that relates the

amount of light emitted from the monitor to the 256 different gray levels in the dig-

ital image is called the gamma curve. There are several different standard gamma

curves in common use. They all follow a power law of the following form:

b = v

where b is the brightness of the light emitted from the screen, v is the gray levelvalue in the image and is the monitor gamma. The standard value for that most

closely approximates the response of the human eye is 2.22. This is the value used

by the television industry for storing and displaying video images. The prepress


10/17


Viewing Images on a Monitor

industry has standardized on a value of 1.8 which more closely corresponds to the

characteristics of printing presses. Macintosh computers often use the value 1.4 for

some unknown reason, while most uncorrected PC monitors have a gamma of about

2.3.

If an image was designed to be displayed on a monitor with a gamma of 2.2 and the

monitor's actual gamma is set to 1.8, the image will appear too light and washed

out. Conversely, if an image was adjusted to look good using a computer with a

monitor gamma of 1.4 or 1.8 and viewed at 2.2, it will look too dark. For this rea-

son, it is very important to set your computer's monitor to the same gamma setting

as will be used to print it. If gamma is ignored, there is no way to guarantee that

prints will not be too light or too dark.

White Point

Finally, there is an important characteristic of computer monitors called white

point. This is usually given as a color temperature and for most uncorrected moni-

tors, it run about 9300 degrees. What this means is that the white that is displayed

on the monitor when you send it maximum values of red, green, and blue has a dis-

tinctly bluish cast. If you were going to view your prints under a light of this same

color temperature, you would get a good match (all other variables being set prop-

erly). Different lights like incandescent, quartz halogen, fluorescent, and daylight

(morning, evening, indirect, etc.) all have different color temperatures and prints

viewed using these different lighting conditions will look radically different. The

standard white point used in the graphic arts industry is a 5000 degree color temper-

ature and most light boxes are set to roughly this color. Viewing prints under fluo-

rescent lighting can be particularly deceptive as mercury vapor lamps has severalspikes in the green part of the spectrum whereas daylight has a relatively smooth

spectrum. This can give rise to considerable variation in certain colors.

Two monitors which use the same phosphors, are both viewed in subdued light,

have their gamma set the same, have their brightness control set properly, and have

the same white point, should produce nearly identical displays.


11/17



Color Spaces

A color space is a mathematical system for representing colors. Since it takes at

least three independent measurements to determine a color, most color spaces are

three-dimensional. Many different color spaces have been created over the years in

an effort to categorize the full gamut of possible colors according to different char-

acteristics. Picture Window uses three different color spaces:

RGB

Most computer monitors work by specifying colors according to their red, green,

and blue components. These three values define a 3-dimensional color space call

the RGB color space. The RGB color space can be visualized as a cube with red

varying along one axis, green varying along the second, and blue varying along the

third. Every color that can be created by mixing red, green, and blue light is located

somewhere within the cube. The following images show the outside of the RGBcube viewed from two different directions:

The eight corners of the cube correspond to the three primary colors (Red, Green,

Blue), the three secondary colors (Cyan, Magenta, Yellow) and black and white. All

the different neutral grays are located on the diagonal of the cube that connects the

black and the white vertices.


12/17


Color Spaces

HSV (Hue Saturation Value)

The HSV color space attempts to characterize colors according to their hue, satura-

tion, and value (brightness). This color space is based on a so-called hexcone model

which can be visualized as a prism with a hexagon on one end that tapers down to asingle point at the other. The hexagonal face of the prism is derived by looking at

the RGB cube centered on its white corner. The cube, when viewed from this angle,

looks like a hexagon with white in the center and the primary and secondary colors

making up the six vertices of the hexagon. This color hexagon is the one Picture

Window uses in its color picker to display the brightest possible versions of all pos-

sible colors based on their hue and saturation. Successive crossections of the HSV

hexcone as it narrows to its vertex are illustrated below showing how the colors get

darker and darker, eventually reaching black.

HSL (Hue Saturation Lightness)

The HSL color space (also sometimes called HSB) attempts to characterize colors

according to their hue, saturation, and lightness (brightness). This color space is

based on a double hexcone model which consists of a hexagon in the middle that

converges down to a point at each end. Like the HSV color space, the HSL space

V = 100% V = 75% V = 50% V = 25%


13/17



goes to black at one end, but unlike HSV, it tends toward white at the opposite end.

The most saturated colors appear in the middle. Note that unlike in the HSL color

space, this central crossection has 50% gray in the center and not white.

Continuous Tone vs. Halftone Images

There are many different technologies used to reproduce photographic images.

Some printing technologies such as laser and ink jet printers work by creating indi-

vidual dots, each of which is one of a small number of solid colors. For example, a

black and white laser printer can only print black or white pixels -- it cannot pro-

duce gray dots. To create the illusion of a photographic image, these tiny dots mustbe clustered in different proportions to reproduce the different colors and gray lev-

els in the image. This dot clustering process is called halftoning or dithering and it

can be done in many different ways.

Devices such as computer monitors, dye sublimation printers, and film recorders cancreate dots of any color without halftoning, and these are called continuous toneprinters because they can reproduce a continuous range of gray levels or colors.

L = 25% L = 50% L = 75%

continuous tone ordered dither error diffusion

image halftone halftone


14/17


How images are digitized

Because a continuous tone printer packs more information into each dot, to achieve

comparable image quality, printers that use halftoning or dithering require higher

resolution, by a factor of roughly 6-8. Thus a continuous tone printer that outputs

images at 200 dpi is roughly similar in quality to a halftone printer that outputs pix-els at roughly 1200-1600 dpi. For this reason, even a 600 dpi laser printer makes

relatively coarse images equivalent to only about 75 dpi continuous tone output.

For printed output to appear photographic when viewed from a standard distance of

about 10 inches requires between 150 and 300 dpi. At 150 dpi, most images will

appear noticeable soft, while between 200 and 300 dpi the incremental improve-

ment is quite small. Beyond 300 dpi there is still some improvement, but for most

images and most observers, it will be virtually unnoticeable.

How images are digitized

The process of converting an image to pixels is called digitizing or scanning and

this function can be performed in many different ways.

Film Scanners

This type of scanner is sometimes called a slide or transparency scanner. They are

specifically designed for scanning film, usually 35mm slides or negatives, but some

of the more expensive ones can also scan medium and large format film. These

scanners work by passing a narrowly focused beam of light through the film and

reading the intensity and color of the light that emerges.

Flatbed Scanners

This type of scanner is sometimes called a reflective scanner. They are designed for

scanning prints or other flat, opaque materials. These scanners work by shining

white light onto the object and reading the intensity and color of the light that is

reflected from it, usually a line at a time. Some flatbed scanners have available

transparency adapters, but for a number of reasons, in most cases these are not very

well suited to scanning film. On the other hand, flatbed scanners can be used as a

sort of lensless camera to directly digitize flat objects like leaves.


15/17



Digital Cameras

One of the most direct ways to capture an image is a digital camera which uses a

special semiconductor chip called a CCD (charge coupled device) to convert light

to electrical signals right at the image plane. The quality of the images created inthis manner is closely related to the number of pixels the CCD can capture. Afford-

able digital cameras suffer from relatively low resolution, limited dynamic range,

and low ISO film speed equivalent, and consequently do not always produce high

quality digital images. To get images with quality comparable to film photography

currently requires very expensive digital cameras.

Video Frame Grabbers

This type of scanner uses a video camera to capture a scene or object and then con-

verts the video signal that comes out of the camera to a digital image in your com-

puter memory. A video camera can be used to digitize scenes containing 3-

dimensional objects, but they usually have much lower image quality than film or

flatbed scanners.

Scanning Services

Photo CD is a service started by Kodak a number of years ago whereby your film

can be scanned using a high quality scanner and written to a compact disk you com-

puter can access. Using Photo CD service is an inexpensive way to get high quality

scans of your images without purchasing a scanner.

Many other scanning services are available which can scan prints or film to floppy

disks or removable disk cartridges. These vary from low resolution snapshot qualityimages to professional drum scans at very high resolution.


16/17

Making f ine pr int s in your digit al dar kr oomPixels, images, and f ilesby Norman Koren

Adigital image is a rectangular grid ofpixels, or "picture elements," illustrated by the image on

the right, which consists of 52x35 pixels; 1820 total. It has been enlarged 5x (to 260x175 pixels) tomake the pixels visible. Pixels appear as squares when enlarged in this way.

Digital images exist as an array of bytes in a computer's RAM memory or asfiles in memory

cards, hard drives, and CDs or DVDs. Several popular file formats are described below.

Each pixel typically consists of 8 bits (1 byte) for a Black and White (B&W) image or 24 bits (3 bytes) for a color image-- one byte each for Red,

Green, and Blue. 8 bits represents 28

= 256 tonal levels (0-255). 16-bit B&W and 48-bit color image formats are also available; each pixel represents216 = 65,536 tonal levels. Editing images in 16/48-bits produces the highest quality results; you can save images in 8/24 bits after editing is

complete. An image'sresolution is the total number of pixels, e.g., 1600 x2000 = 3.2 Megapixels, which corresponds to 3.2 Megabytes inside yourcomputer for 8-bit B&W images or 9.6 Megabytes for 24-bit (3 bytes/pixel) color images. There are several other definitions of "resolution." See the

explanation below.

Digital images are obtained fromdigital cameras or byscanning film or prints. Scanners are specified by their dpi or ppi resolution-- dots (actually,

pixels) per inch they can obtain from the source. Scanning the original source-- the negative or slide-- always produces better quality than scanning a

print. Printers are specified by their dpi (dots per inch) "resolution," typically 720, 1440 or 2880 for Epson. This number is the stepper motor pitch,

not the actual visual resolution. It typically requires several printer dots to represent one image pixel. You don't need to worry about the

correspondence between image pixels and printer dots; this is handled by the image editor and printer driver software.

Image resolution and print size

Considerable confusion arises because image size is specified by the number of pixels, the

"resolution" in dots or pixels per inch (dpi or ppi), and the physical size (width and height).But

the only attribute that counts is the number of pixels.

The image on the left was taken on the Canon EOS-10D, converted from RAW using the Canon

File Viewer Utility (which I've since replaced with Capture One DSLR LE), adjusted for color

(though far from finished), then resized to 260x175 pixels wide in my favorite image editor,Picture Window Pro.

.

Picture Window Pro

.

The dialog box used to resize the image in is shown on the right. The original (Current)

image is 3072 pixels wide and 2048 pixels high-- straight out of the EOS-10D. The 180 dpi

"Resolution" (strictly speaking, it should be ppi--pixels per inch) is set when the image is

converted from RAW format. This number is arbitrary and has no effect on image quality.

It is informational only. The same holds for the Width of 17.07 inches and Height of 11.38

inches. It is calculated from the equation,

size = pixels/dpi (or pixels/ppi)

It make no difference whether the image is 3437 dpi, 22.7x15.1 mm (the actual size of the

EOS-10D digital sensor) or 17.07 dpi, 15x10 feet (a billboard); each of the 3072x2048 (6.3million) pixels (6.3 megapixels) is exactly the same. I didn't change the Resolution (dpi

setting) when I resized the image, hence the "size" of the new 200x133 pixel image size is

tiny: 1.11x0.74 inches. This "size" is completely unrelated to the size you see on yourmonitor.

To add to the confusion, the word "Resolution" has several meanings. It can be the highest

spatial frequency where a line pattern is visible: See the series on Image sharpness and MTF. It often refers to the total pixel count of an image, e.g.,

3072x2048 pixels for the EOS-10D. I prefer eitherof these definitions to the dpi/ppi setting, which has nothing to do with the total detailpresent in an image, and which can be changed without changing a single pixel. But we're stuck with it in image editing programs.

You can easily change Resolution (dpi), hence Width and Height, without changing pixel count, i.e., you canrescale the image withoutresizing (i.e.,

resampling) it. In Picture Window Pro, open the Resize dialog box (above), click on the arrow to the right of the Preserve, then select File Size

and Proportions. When you can change either Width, Height, or Resolution (dpi), the other two follow. In Photoshop, open the Image Size

dialog box, shown below, and leave Resample Image unchecked. CheckResample Image if you want to change the pixel count-- toresize theimage.

Picture Window Pro

If you right-click on the image in Picture Window Pro, then click on Display

info, the Window Info box appears. The properties of the resized 200x133 pixelimage are shown on the left. The Size numbers are the same as the New column

in Resize dialog box, above. But the File Size, 8,305 pixels, is much smallerthan the 79,800 byte image size (200x133 pixels x 3 bytes/pixel). This is the

result ofJPEG compression. GIF and PNG files are also compressed, but TIFF

files are not: Image and file sizes are the same. I usually sharpen an image

(using the simple Sharpen transformation,with Amount around 70%) after

resizing it down.

In Picture Window Pro you select the print size when you print. The Width and Height attributes are ignored. This doesn't exactly hold for

Photoshop.

.

Photoshop 6.0

.

Photoshop's default Print... command tries to print images at the specified

Width and Height. When you try to print the original 17.07x11.38 inchimage on letter-sized paper, an annoying message appears, "The image is

larger than the paper's printable area; some clipping will occur." There are

two solutions.

1. You canrescale the image using the Image Size dialog box,

according to the instructions above. You rarely need toresize it.

2. Click on Print Options... instead ofPrint... in Photoshop 6 (Printwith Preview... in Photoshop CS). The first time you open this box

for an image, Scale is set to 100% and Scale to Fit Media is

unchecked. If you checkScale to Fit Media, Scale is adjusted so

the image fits the page. You may need to clickPage Setup... toadjust borders and orientation (Portrait or Landscape). Or you can

leave Scale to Fit Media unchecked and manually set Scale. A

small page preview in the Print Options box helps with the setting, which will be remembered as long as the image remains open.

How many pixels to you need for a sharp print?

Print PPI Perceived print quality

300 Outstanding. As sharp as most printers can print; about as sharp as the eye can see at normal viewing distances.

200Excellent. Close to 300 PPI for small prints, 8x11 (or A4) and smaller.

Outstanding quality in large prints, 11x17" (or A3) and larger, which tend to be viewed from greater distances.

150 OK for large prints. Adequate, but not optimum, for small prints.

100 Adequate, but not optimum, for large prints. Mediocre for small prints.

300 pixels per inch (ppi) is about as sharp as the eye can see on an inkjet print; it can be very impressive in a print from a sharp image file.

Remember,these numbers are actual pixels per inch on the print, not the ppi setting of the image file.

When an image is sent to the printer, the image editor or printer driver resizes it to the printer's native resolution-- 720 dpi for Epson Photo printers;600 dpi for HP and Canon. No manual resizing is required. There is some controversy about how good a job image editors do (particularly

Photoshop). Read Qimage Print Quality Challenge to learn more. I'm pleased with the results I get from Picture Window Pro.

Most digital images must be resized down for the monitor display-- for web pages or e-mail. Many people are careful to scale the resized images to

72 dpi.Absolutely unnecessary. I know of no web browser or viewing software that pays any attention to the dpi setting. Most monitors actually

display 80-100 pixels per inch, anyway.

Image file formatsSeveralfile formats are available for image storage. The most important are TIFF,JPEG, GIF, andPNG. The primary difference between them is

the type and amount ofimage compression. Compression reduces the amount of storage space required by an image. For example, a 1600x2000pixel 24-bit color image (3 bytes per pixel) requires 9.6 megabytes to store without compression; it requires considerably less with compression.

There are two types of compression.

q Lossless compression maintains all image detail, bit-by-bit. Typical compression ratios are 30-50%, depending on the detail in the image.

The finer the detail, the less the compression. Lossless compression is used by the PNG format. It is available, though rarely used, with the

TIFF format.

q Lossy compression sacrifices detail in order to achieve higher compression ratios. The amount of compression depends on the detail in the

image and the quality level selected when the image is saved. JPEG and GIF use different types of lossy compression.

In addition to the standard formats, many digital cameras have the option of storing images inRAWformat-- unaltered data straight out of the image

sensor. The information in RAW files replicates the mosaic pattern of the Bayer filter arrays used in most digital cameras. RAW files do notconform to any standard; they are unique to each camera and manufacturer. Canon calls them CRW; Nikon calls them NEF. They must be converted

to a standard format by a RAW converter (or de-mosaicing program) before they can opened by an image editor. I discuss RAW conversion for the

Canon EOS-10D here; I explain how to use RAW files to obtain a significant quality advantage in Tonal quality and dynamic range in digital

cameras.

The image on the right is used as to illustrate compression. It is a 24-bit color 260x175 pixel image(3 bytes per pixel), and therefore contains 136,500 bytes (136.5 kB). It was stored as a 100%

Quality JPEG, 46.3 kB in size. The compression ratio is 136.5/46.3 = 2.95x. 100% JPEGs arevirtually indistinguishable from uncompressed TIFF images-- they contain a tiny loss that would

only become visible after the file was repeatedly opened and saved. The storage required for this

image in each format is shown below in (bold blue).

Web browsers support JPEG, GIF, and PNG formats, but not TIFF.

q TIFF files (identified by the .tif extension) are normally uncompressed. Lossless compression is available, but not universally supported.

TIFF is highly versatile; it can store 16/48-bit images andmetadata, such as Description, Artist's name, and Copyright, in tagged fields. This

makes TIFF files slightly larger than the images they contain. TIFF is the format of choice for saving images intended for high quality

printed output.(138.5 kB)

q PNG (.png) is another format worth considering. It uses lossless compression: image quality is equal to TIFF but file size can be considerably

smaller, though generally larger than JPEG. PNG is supported by most web browsers and image editors, but it isn't widely used-- it's

undoubtedly the most underrated image file format. I occasionally use it for Web display of Black & White images, such as the gamma testpattern, because it compresses almost as well as JPEG, which doesn't support B&W. PNG was created to circumvent the LZW patent used in

GIF and TIFF formats. (96.3 kB; 1.42x)

q GIF (.gif) is best for Web display of block graphics and charts. Its limited color palette makes it a poor choice for high-quality photographic

images, although it's often used for thumbnails. GIF files can be very compact; they lack the wavy edge artifacts of JPEG files (38.2 kB; 3.6x)

q JPEG (.jpg) is the most popular format for Web display of photographic images. Its principal feature is lossy compression, which can result

in artifacts, most notably a wavy appearance near boundaries. The loss in quality and the stored image size depends on the Quality setting

used to save the image. Higher quality JPEGs are larger but have more detail and fewer artifacts. JPEGs typically range from 1/5 to 1/25 the

size of TIFFs. This is illustrated below for an image saved by Picture Window Pro with JPEG quality levels of 90%, 70%, and 30%.

File formats are discussed in more detail in A few scanning tips by Wayne Fulton. Irfanview is a great free utility that can read and write image filesin almost any format.

The images below illustrate the effects of the JPEG Quality

setting on image compression with Picture Window Pro. The

dialog box is shown on the right. I use quality levels between

about 80 and 95% for most images in this site.

90% quality; 15.3 kB; 8.9x.Quality is closeto 100%, but a little waviness-- the classic

JPEG artifact-- is visible in the sky near the

trees.

70% quality; 8.9 kB; 15.3x. Image quality isstill pretty good, but wavy artifacts are

significantly worse and detail in the rocks is

reduced.

30% quality; 6.1 kB; 22.4x. Image quality isquite poor. Wavy artifacts are obvious; there

is significant loss of detail, and square zones

are visible in the sky.

Image quality and size vs. Quality setting for JPEG images

Every program has its own JPEG Quality settings; there is no universal standard. Photoshop has settings between 0 and 12. IrfanView (a handy little

editing utility) has settings between 0 and 100. The relationship between settings in different programs is anything but linear. PW Pro Quality = 70%

(8.9 kB) is roughly equivalent to Irfanview Quality = 50% (7.9 kB) and Photoshop Quality = 3 (33 kB in Photoshop CS; 13.8 kB in Photoshop 6).

Photoshop files are considerably larger, even though have no embedded ICC profiles, perhaps because they have extra space reserved for Exif data

(digital camera settings). This can be a disadvantage for small images used for Web display.

Many digital cameras store images in JPEG format. This can lead to problems because image quality can deteriorate rapidly when images are saved

and reloaded in JPEG format.JPEGs should be used with extreme caution for images intended for high quality quality printed output. If possible

they should be avoided altogether. If you plan to do much editing on a JPEG image, it's best to convert it to TIFF. No quality is lost when images are

stored and reloaded in TIFF format.

Additional file formats You may occasionally encounter these, but they're not recommended for general use.

Macintosh users should add the appropriate three leter suffix (JPG, TIF, PNG, etc.) to file names to make it easier for us Windows users to read.

q JPEG 2000 An update of JPEG that offers a higher degree of compression at the same image quality level as well as an option for lossless

compression. It also has options for fast display when full resolution isn't needed. It should be an excellent format once it's widely adapted,

but few web browsers support it as of early 2004. I wouldn't use it until all major web browsers (Internet Explorer, Mozilla, and the Mac

browsers) have supported it for at least a year.

PSD Adobe Photoshop Document. Designed by Adobe for use within Photoshop; not supported by web browsers and most image editors. Itsould not be used for file interchange. To be used with programs other than Photoshop, PSD files generally have to be transformed into a

standard format such as TIFF. Irfanview is a great little program for translating them.

q BMP Windows bitmap format. A widely-supported uncompressed format that lacks the versatility of TIFF. TIFF should be used in its place.

There are about three dozen additional formats, most of which you'll never encounter. The Graphics File Formats Page describes many of them in

gory detail. Kodak has a tutorial on file formats that promotes their technically-excellent proprietary formats and mostly ignores standard formats.

Another reminder of how this once-great company has fallen from grace.

Back to Making fine prints... Getting started | Calibrating your monitor

.

Scanners

Pixels and images

it

Google Search

it
http://-/?-http://www.normankoren.com/makingfineprints.html#Why48http://-/?-http://www.normankoren.com/digital_cameras.htmlhttp://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/Tutorials/MTF3.htmlhttp://www.normankoren.com/EOS-10D.htmlhttp://www.normankoren.com/EOS-10D_2.html#C1_DSLR_LEhttp://www.dl-c.com/http://www.normankoren.com/Tutorials/MTF.htmlhttp://-/?-http://www.ddisoftware.com/qimage/quality/http://www.normankoren.com/EOS-10D_2.html#Rawhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.libpng.org/pub/png/pngintro.htmlhttp://www.scantips.com/basics09.htmlhttp://www.irfanview.com/http://www.irfanview.com/http://www.irfanview.com/http://www.dcs.ed.ac.uk/home/mxr/gfx/2d-hi.htmlhttp://www.kodak.com/US/en/digital/dlc/book2/chapter4/intro.shtmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/makingfineprints1A.htmlhttp://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/index.htmlhttp://www.normankoren.com/contact_news.htmlhttp://www.normankoren.com/sitemap.htmlhttp://www.normankoren.com/makingfineprints1A.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.kodak.com/US/en/digital/dlc/book2/chapter4/intro.shtmlhttp://www.dcs.ed.ac.uk/home/mxr/gfx/2d-hi.htmlhttp://www.irfanview.com/http://www.irfanview.com/http://www.irfanview.com/http://www.scantips.com/basics09.htmlhttp://www.libpng.org/pub/png/pngintro.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/EOS-10D_2.html#Rawhttp://www.ddisoftware.com/qimage/quality/http://-/?-http://www.normankoren.com/Tutorials/MTF.htmlhttp://www.dl-c.com/http://www.normankoren.com/EOS-10D_2.html#C1_DSLR_LEhttp://www.normankoren.com/EOS-10D.htmlhttp://www.normankoren.com/Tutorials/MTF3.htmlhttp://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/digital_cameras.htmlhttp://-/?-http://www.normankoren.com/makingfineprints.html#Why48http://-/?-http://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/printers.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/PWP_Providence.htmlhttp://www.normankoren.com/PWP_hand_color.htmlhttp://www.normankoren.com/PWP_contrast_masking.htmlhttp://www.normankoren.com/PWP_masks.htmlhttp://www.normankoren.com/PWP_intro.htmlhttp://www.normankoren.com/color_management_4.htmlhttp://www.normankoren.com/color_management_3.htmlhttp://www.normankoren.com/color_management_2.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/matting_framing.htmlhttp://www.normankoren.com/makingfineprints4.htmlhttp://www.normankoren.com/makingfineprints3.htmlhttp://www.normankoren.com/makingfineprints2.htmlhttp://www.normankoren.com/printer_calibration.htmlhttp://www.normankoren.com/makingfineprints1A.htmlhttp://www.normankoren.com/paper_ink.htmlhttp://www.normankoren.com/printers.htmlhttp://www.normankoren.com/digital_cameras.htmlhttp://-/?-http://-/?-http://-/?-http://-/?-http://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/glivre/index.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.adorama.com/Refby.tpl?refby=rflAID016047http://www.adorama.com/Refby.tpl?refby=rflAID016047http://www.amazon.com/exec/obidos/redirect-home/normankorenph-20http://www.amazon.com/exec/obidos/redirect-home/normankorenph-20http://www.amazon.com/exec/obidos/redirect-home/normankorenph-20http://www.amazon.com/exec/obidos/redirect-home/normankorenph-20http://www.normankoren.com/webpages.htmlhttp://www.normankoren.com/EOS-10D.htmlhttp://www.normankoren.com/Tutorials/MTF7.htmlhttp://www.normankoren.com/Tutorials/Epson_flatbeds.htmlhttp://www.normankoren.com/Tutorials/Canoscan4000.htmlhttp://www.normankoren.com/Tutorials/Canoscan4000.htmlhttp://www.normankoren.com/zonesystem.htmlhttp://www.normankoren.com/PWP_intro.htmlhttp://www.normankoren.com/phototechnique.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/Tutorials/MTF.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/contact_news.html#Newshttp://www.normankoren.com/contact_news.htmlhttp://www.normankoren.com/sitemap.htmlhttp://www.normankoren.com/index.html


17/17

Making f ine pr int s in your digit al darkr oom

Light and color : an int r oduct ionby Norman Koren

Getting started | Scanners | Pixels,

images, & files

Light & color

Rhode Island

This page introduces the basic concepts of light and color. Color theory is dealt with in more depth in the series on

Color management.

Light and ColorWe begin with a review of light and color. The concepts presented here-- additive and subtractive color and their

respective primaries-- are critically important for image editing. You may skip to the next section if you are familiar

with them.

The human eye is sensitive to

electromagnetic radiation with

wavelengths between about 380

and 700 nanometers. This

radiation is known as light. The

visible spectrum is illustrated onthe right. The eye has three classes

of color-sensitive light receptors

calledcones, which respond

roughly to red, blue and green

light (around 650, 530 and 460

nm, respectively). A range of

colors can be reproduced by one

of two complimentary approaches:

q Additive color: Combine lightsources, starting with darkness (black). Theadditive primary colors are red

(R), green (G), and blue (B). Adding R and G light makes yellow (Y). Similarly, G + B = cyan (C) and R + B

= magenta (M). Combining all three additive primaries makes white.

q Subtractive color: Illuminate objects that contain dyes or pigments thatremove portions of the visible

spectrum. The objects may either transmit light (transparencies) or reflect light (paper, for example). The

subtractive primaries are C, M and Y. Cyan absorbs red; hence C is sometimes called "minus red" (-R).

Similarly, M is -G and Y is -B. The two approaches are illustrated on the right and described in the table

below.

Unfortunately, ideal C, Y and M inks don't exist; the subtractive primaries don't entirely remove their compliments

(R, B and G). This isn't a problem for film, where light is transmitted through three separate dye layers, but it has

important consequences for prints made with ink on reflective media (i.e., paper). Combining C, Y and M usually

produces a muddy brown. Black ink (K) must added to the mix to obtain deep black tones. CMYK color is highly

device dependent-- there are many algorithms for converting RGB to CMYK. Photographic editing should be done in

RGB (or related) color spaces. Conversion to CMYK (usually with colors added to extend the printer color gamut)

should be left to the printer driver software.

Addit ive color Subt r act ive color

Light sources: beams of light or dots oflight on monitor screens

Objects that transmit or reflect light:film or prints.Typically illuminated by white light.

Primaries:Red (R), Green (G), Blue (B) Primaries: Cyan (C), Magenta (M), Yellow (Y)

Light from independent sources is added.Portions of the visible light spectrum are absorbed byinks, which contain dyes or pigments, or by dye layers

in photographic film or paper.

Adding red and green makes yellow (R + G

= Y); Similarly, G + B = C and R + B = M.Adding all three additive primaries inroughly equal amounts creates gray or

white light.

Each subtractive primary removes one of the additiveprimary colors from the reflected or transmitted image.Cyan (C) removes red; hence it is known as minus red(-R). Similarly, M is -G and Y is -B. Objects are

typically illuminated by white light. Combining twosubtractive primaries makes an additive primary (seeillustration). Combining all three subtractive primaries

in roughly equal amounts creates gray or black.

You can obtain a wide range of colors, but not all the colors the eye can see, by combining RGB light. The gamutof

colors a device can reproduce depends on the spectrum of the primaries, which can be far from ideal. To complicate

matters, the eye's response doesn't correspond exactly to R, G and B, as commonly defined (the description above is

oversimplified). Device color gamut and the eye's response are discussed in detail in the page on Color Management.

Color modelsIf you lighten or darken color images you need to understand how color is represented. Unfortunately there are

several models for representing color. The first two should be familiar; the latter two may be new.

q RGB - Red, Green, Blue; The additive primary colors. Used for monitor screens and most image file formats.

There are actually a number of RGBcolor spaces-- sRBG, Adobe RGB 1998, Bruce RGB, Chrome 2000,

etc.-- differing from each other in the purity of their primary colors, which affects theirgamut-- they range of

colors they represent. They are discussed in Color Management.

q CMY(K) - Cyan, Magenta, Yellow; The subtractive primary colors: the compliments of the additive

primaries (Cyan is -red; magenta is -green; yellow is -blue.) Widely used in inks for printing with black (K)added because C, Y, and M pigments and inks rarely give deep, rich black tones by themselves (they tend to

make a muddy brown). CMYK is important to the prepress industry, but most photographers don't need to be

concerned with it. Most high quality photographic printers have additional inks (light M, light C and gray may

be added to the basic four), so they aren't really CMYK; the printer driver software converts RGB files into

ink densities.

q HSV - Hue, Saturation, Value. Hue is what we perceive as color. S is saturation: 100% is a pure color. 0% is a

shade of gray. Value is related to brightness. HSV and HSL (below) are obtained by mathematically

transforming RGB. HSV is the identical to HSB.

q HSL - Hue, Saturation, Lightness. H is the same as in HSV but L and V are defined differently. S is similar

for dark colors but quite different for light colors. Also called HLS.

It is not practical to use RGB or CMY(K) to adjust brightness or color saturation because each of the three color

channels would have to be changed, and changing them by the same amount to adjust brightness would usually shift

the color (hue). HSV and HSL are practical for editing because the software only needs to change V, L, or S. Image

editing software typically transforms RGB data into one of these representations, performs the adjustment, then

transforms the data back to RGB. You need to know which color model is used because the effects on saturation are

very different.

HSV color is shown here in an

illustration from Jonathan Sachs'tutorial, "The Basics of Digital

Images" (right click on the link to save

it in Adobe PDF format). V = max(R,G,

B). Maximum Value (V = 1 or 100%)

corresponds to pure white (R=G=B=1)

and to any fully saturated color (at least

one RGB value at 1 and one at 0; no

gray component (W = min(R,G,B)). V

= 0 is pure black, regardless of H and S.

The HSV color model can be depictedas acone, widest at the top (V = 1),

coming to a point at the bottom (V = 0;

pure black). (I use the "V"-like

appearance of the cone as a mnemonic

to remember "HSV." The names of the

color models are pretty arbitrary.) efg

has a technically detailed explanation

of the HSV color model, complete with

a Java applet.

HSL color. Maximum color saturation takes placeat L = 0.5 (50%). L = 0 is pure black and L = 1

(100%) is pure white, regardless of H or S. The

HSL color model can be depicted as adouble cone,

widest at the middle (L = 0.5), coming to points at

the top (L = 1; pure white) and bottom (L = 0; pure

black).

Now the important part. What you must remember about the HSV and HSL color models is,

Darkening in HSV reducessaturation. Darkening in HSL increasessaturation when

L > 0.5.

Lightening in HSV increasessaturation. Lightening in HSL reducessaturation when L

> 0.5.

HSVBest representation of saturation

HSLBest representation of lightness

HSV and HSL were developed to represent colors in systems with limited dynamic range (pixel levels 0-255 for 24-

bit color). The limitation forces a compromise. HSV represents saturation much better than brightness: V = 1 can be

a pure primary color or pure white; hence "Value" is a poor representaton of brightness. HSL represents brightness

much better than saturation: L = 1 is always pure white, but when L > 0.5, colors with S = 1 contain white, hence

aren't completely saturated. In both models, hue H is unchanged when L, V, or S are adjusted.

HSV and HSL are illustrated above for red (H=0). S varies from 0 to 1 along the horizontal axis; V and L vary from

0 to 1 along the vertical axis. The right side of the HSV illustration (S=1) always has maximum saturation (G=B=0)

but the top (V=1) varies from pure white at S=0 to pure red at S=1. The top of the HSL illustration (L=1) is pure

white for all values of S. It would be nice to be able to represent brightness and saturation properly in one system, but

you can't have it both ways.

Transformations for adjusting brightness and saturation in Picture Window Pro let you choose between HSV and

HSL. HSV is the default. I usually prefer HSL when the primary intent of the transformation is to adjust brightness; I

sometimes prefer HSV when the primary intent is to adjust saturation (I work with brightness more often). But I'm

not rigid about these preferences; I often try out both to see how they appear in the Preview window. I don't

recommend HSL when you want to darken white or nearly white tones. They can take on an unnatural color cast.

SHSV = 1

Relationship between RGB, HSV, and HSL color representation for math geeks

H is the same for HSV and HSL. We won't give the equations here; you can find them in efg's HSV

lab report. Expressed in degrees (0-360) for any nonzero x, H = 0 for Red (x,0,0); 60 for Yellow (x,

x,0), 120 for Green (0,x,0) (illustrated below), 180 for Cyan (0,x,x), 240 for Blue (0,0,x), and 300

for Magenta (x,0,x). H can also be represented on a scale of 0 to 1.

Assume R, G, and B can have values between 0 and 1. Let W = min(R,G,B) = the gray component.

HSV (HSB) HSL (HLS)

V = max(R,G,B) L = (V+W)/2

SHSV = (V-W) / V

SHSL = (V-W) / (V+W) = (V-W) / (2L) ; L

0.5

Any color with R, G, or B = 1 has V = 1.

Maximum saturation occurs when W = 0.

A bright, fully saturated color (max(R,G,B) = V =1; min(R,G,B) = W = 0; SHSV = SHSL = 1) must

have L = 0.5. L = 1 corresponds to pure white.

V, L, and S illustrated for H = 0.333 (120; Green)

HSV: Best representation of saturation

HSL: Best representation of lightness

V, L, and H illustrated for S = 1 (maximum saturation)

The Y, C, and M bands are much narrower than the R, G, and B bands. I'm not sure why; I suspectit results from specific properties of HSL and HSV (where V = max(R,G,B) rather than, say, mean

(R,G,B).). Y, C, and M appear brighter than R, G, and B at similar V and L levels because both Vand L are related to max(R,G,B).

Some interesting relationships

(1) For W = min(R,G,B) = 0 (no gray; maximum saturation), SHSL = SHSV = 1 ; L = V / 2 ; L

= 0.5

These relationships imply that (1) the bottom half of the HSL L-H plot for S=1 (above, right) isidentical to the HSV V-H plot for S=1 (above, left), and (2) the top half of the HSL S-H plot is

identical to an HSV S-H plot for V=1 (not shown), i.e., the HSL L-H plot (above, right)

combines twoHSV plots.

All saturation equations have V-W in the numerator; they differ in denominator scaling. In bothrepresentations, S is a measure of relativesaturation. S is 0 when W = V (R = G = B; neutral gray); S

= 1 when W is at its minimum allowable value for a given value of V or L. For HSV, W = 0 when S =

1.

For HSL with L 0.5, W must be greater than 0. Maximum saturation takes place when W = 2L-V takes itsminimum value, W

min. In this case V = 1, so W

min= 2L-1. S

HSL= (V-W) / (2-V-W) = (1-2L+1) / (2-1-

2L+1) = 1.

V and L don't correspond with perceived luminance; for example, blue and gray or white with thesame V or L values would have very different luminance. The PAL luminance signal, Y = 0.30R +0.59G + 0.11B, corresponds more closely to perceived luminance.

.

View image galler ies

How t o pur chase print s.

.

.

An excellent oppor t unit y t o collect high qualit yphot ogr aphic pr int s and suppor t t his websit e

.

Google Search
http://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/PWP_Providence.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.efg2.com/Lab/Graphics/Colors/HSV.htmhttp://www.dl-c.com/http://www.efg2.com/Lab/Graphics/Colors/HSV.htmhttp://www.efg2.com/Lab/Graphics/Colors/HSV.htmhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/index.htmlhttp://www.normankoren.com/contact_news.htmlhttp://www.normankoren.com/sitemap.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.efg2.com/Lab/Graphics/Colors/HSV.htmhttp://www.efg2.com/Lab/Graphics/Colors/HSV.htmhttp://www.dl-c.com/http://www.efg2.com/Lab/Graphics/Colors/HSV.htmhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/PWP_Providence.htmlhttp://www.normankoren.com/PWP_Providence.htmlhttp://www.normankoren.com/PWP_hand_color.htmlhttp://www.normankoren.com/PWP_hand_color.htmlhttp://www.normankoren.com/PWP_contrast_masking.htmlhttp://www.normankoren.com/PWP_masks.htmlhttp://www.normankoren.com/PWP_intro.htmlhttp://www.normankoren.com/color_management_4.htmlhttp://www.normankoren.com/color_management_3.htmlhttp://www.normankoren.com/color_management_2.htmlhttp://www.normankoren.com/color_management.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/digital_tonality.htmlhttp://www.normankoren.com/matting_framing.htmlhttp://www.normankoren.com/matting_framing.htmlhttp://www.normankoren.com/makingfineprints4.htmlhttp://www.normankoren.com/makingfineprints3.htmlhttp://www.normankoren.com/makingfineprints2.htmlhttp://www.normankoren.com/printer_calibration.htmlhttp://www.normankoren.com/makingfineprints1A.htmlhttp://www.normankoren.com/paper_ink.htmlhttp://www.normankoren.com/paper_ink.htmlhttp://www.normankoren.com/printers.htmlhttp://www.normankoren.com/digital_cameras.htmlhttp://-/?-http://-/?-http://www.normankoren.com/scanners.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/glivre/index.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.adorama.com/Refby.tpl?refby=rflAID016047http://www.adorama.com/Refby.tpl?refby=rflAID016047http://www.amazon.com/exec/obidos/redirect-home/normankorenph-20http://www.amazon.com/exec/obidos/redirect-home/normankorenph-20http://www.normankoren.com/webpages.htmlhttp://www.normankoren.com/EOS-10D.htmlhttp://www.normankoren.com/EOS-10D.htmlhttp://www.normankoren.com/Tutorials/MTF7.htmlhttp://www.normankoren.com/Tutorials/Epson_flatbeds.htmlhttp://www.normankoren.com/Tutorials/Epson_flatbeds.htmlhttp://www.normankoren.com/Tutorials/Canoscan4000.htmlhttp://www.normankoren.com/Tutorials/Canoscan4000.htmlhttp://www.normankoren.com/zonesystem.htmlhttp://www.normankoren.com/PWP_intro.htmlhttp://www.normankoren.com/phototechnique.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/how_to_purchase.htmlhttp://www.normankoren.com/Tutorials/MTF.htmlhttp://www.normankoren.com/Tutorials/MTF.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/makingfineprints.htmlhttp://www.normankoren.com/contact_news.html#Newshttp://www.normankoren.com/contact_news.htmlhttp://www.normankoren.com/sitemap.htmlhttp://www.normankoren.com/index.html

Date post:	06-Apr-2018
Category:	Documents
Upload:	sreejeshrs
View:	214 times
Download:	0 times

Digital.images

Documents