Imaging - McGill University · · 2009-07-10What Is A Digital Image? Digital Image: An image is a...

© 2002 IBM Corporation

Micro & Nanobioengineering Lab

Biomedical Engineering Department

McGill University

| McGill, Nov 2005

[email protected]/djgroup

Imaging

Cecile M. Perrault

Imaging

Viewing Recording Enhancing Using

Importance of

bit depth,

pixel binning

File format

Brightness

Constrast

Colors Guidelines

What Is A Digital Image?

Digital Image: An image is a numerical representation of a

“picture”.

A set of numbers interpreted by the computer which creates a visual representation that is understood by humans.

255 255 199143 97 18732 12 3423 22 11

244 198 179123 94 19532 43 5213 32 11

253 217 23468 185 9713 12 2711 14 26

Courtesy of Nick Beavers, Application Specialist, Media Cybernetics

Image: Pixel Array

Pixels are identified by their position in a grid (two dimensional array), referenced by its row (x), and column (y).

Pixel = Picture Element


Binary Digits (bits)

Bitonal

0 = Black1 = White


What is bit-depth?Bit Depth: Is determined by the number of bits used to define each pixel. The

greater the bit depth, the greater the number of tones (grayscale or color)

that can be represented.


Bits Tones Binary Digits Array

1 bit (21) 2 tones

(0 – 1)

0 or 1

2 bits (22) 4 tones

(0 – 3)

00, 01, 10, 11

3 bits (23) 8 tones

(0 – 7)

000, 001, 010, 011, 100,

101, 110, 111

4 bits (24) 16 tones

(0 – 15)

0000, 0001, 0010, 0100,

1000, 0011, 0101, 1001,

1010, 0111, 1011, 1100,

1101, 1110, 1111, 0110

What is bit-depth?

Bit Depth: Is determined by the number of bits used to define each pixel. The

greater the bit depth, the greater the number of tones (grayscale or color)

that can be represented.

12 bit: 4096 levels (0-4095)16 bit: 65536 levels (0-65535)

1 bit2 levels

2 bit4 levels

3 bit8 levels

4 bit16 levels

6 bit64 levels

8 bit256 levels

Courtesy of Claire Brown, McGill Imaging Facility

What is bit-depth?Bit Depth: Is determined by the number of bits used to define each pixel. The greater the bit depth,

the greater the number of tones (grayscale or color) that can be represented.


In the lab

Binning

Imaging pixels

Conversion 12 bits14 bits16 bits

2x2, 4x4Up to 8x8Up to 8x8

2560 x 1920 imaging pixels



StereomicroscopeConfocal

microscopeInverted

microscope

Pixel Binning

5 7 20 15

6 18 9 7

22 15 6 1

17 11 9 7

36 51

65 23


Pixel Binning

1x1

0.108 µm/pixel

2x2

0.216 µm/pixel

3x3

0.324 µm/pixel

4x4

0.432 µm/pixel

Different contrast and brightness

Same contrast and brightness


Pixel Binning

1x1

0.108 µm/pixel

2x2

0.216 µm/pixel

3x3

0.324 µm/pixel

4x4

0.432 µm/pixel

Same display settings

Different contrast and brightness


Imaging


Importance of

bit depth,

pixel binning

File format

Brightness

Constrast

Colors Guidelines

Recording: what format ?

� JPEG (JPG): lossy format; supports 8 bits per color (R,G,B) for a 24 bit total.

� TIFF: lossless, saves up to 32 bits� PNG: lossless, saves up to 64 bits� GIF: lossless. limited to 8-bit palette. More effective

when large areas are single color.� BMP: uncompressed. Windows-proprietary file.

Save original pictures in TIFF or PNG. Only use JPG forfinal distribution

Imaging


Importance of

bit depth,

pixel binning

File format

Brightness

Constrast

Colors Guidelines

Types of Imaging Software

Capture only or “driver” software: software used to capture and save an image from a device – developed mostly by hardware manufacturersExample: NIS Elements

“Imaging” software, Image Editing, Photo Retouching: software used primarily in home and general business applications, mostly consumer orientedExample: The GIMP (free and open source), Adobe PhotoShop, Microsoft Photo Editor, Image Tools

Basic Image Measurement Software: used for basic image capture, enhancement, with simple measuring toolsExample: Image-Pro Express

General Analytical Image Analysis Software: used in scientific/industrial analysis of images to generate proven dataExample: ImageJ, Image-Pro Plus, Morphometrics

Vertical Market Image Analysis Software: used to solve specific imaging problems in a related industryExample: Array-Pro

ImageJ

� Open source software developed by the NIH

� Widely used by the scientific community and offers a number of available plugins for extra applications ( cell counting, particle tracking ….)

� Download the original ImageJ at: http://rsbweb.nih.gov/ij/

� You also have the option to download the WCIF ImageJversion instead, which comes with a number of pluginsalready installed, useful with biological work: http://www.uhnres.utoronto.ca/facilities/wcif/fdownload.html

� The WCIF version has its own manual : http://www.uhnresearch.ca/facilities/wcif/PDF/ImageJ_Manual.pdf

Image Enhancement: Histogram

� A histogram is a plot of number of pixel for each tonal value

� The higher the bit depth, the better the dynamic range of the image

Black: 0White: 255 for 8-bit images

: 4095 for 12-bit images (2n –1) for n-bit images

Image Enhancement: Brightness

� Brightness: Overall amount of “light” in an image.� Brightness change adds/removes a constant value to all pixels� Shift right or left the histogram

Image Enhancement: Brightness� In

ImageJ:

Image Enhancement: Contrast

� Contrast: The degree of difference between the brightest and darkest components of the image.

� Adjusting the contrast expands or compresses the histogram around the midpoint value

Image Enhancement: Contrast� In ImageJ:

Low Dynamic Range

Medium Contrast

Full Dynamic Range

HighContrast


Image Enhancement: Grey Value/ Histogram stretch

� Expands original input brightness values to make use of total range or sensitivity of output device


� In ImageJ:


� In ImageJ:

Image Enhancement: Colors

� Most images start as a black and white.


� Your image should start as a black and white image:

Should be

either

of those


� Then change the LookUp Table:

DAPI

Cy3

FITC

Merge Images

Image Enhancement: Processing/Color Overlays

Image Enhancement: Processing/Color Overlays� In ImageJ:

– Open each color image



– Choose “Image”, “Color”, “Merge Channels…”




– Assign a color to each image




– Assign a color to each image

– Press OK

Red

Green

Blue


Image Enhancement: Color Separation


� In ImageJ:

– Open image


� In ImageJ:

– Open image

– Select “Image”, “Color”, “Split Channels”


� In ImageJ:

– Open image

– Select “Image”, “Color”, “Split Channels”

Background Automatic flatten of

Background

Original


Image Enhancement: Shading Correction


� In ImageJ:

– Open the image and its background


� In ImageJ:


– Select “Process”, “Image Calculator…” (ensure that images are in 32-bit)


� In ImageJ:



– Divide the original image by its background


� In ImageJ:



– Divide the original image by its background

– Adjust Brightness

Imaging


Importance of

bit depth,

pixel binning

File format

Brightness

Constrast

Colors Guidelines

Imaging Guidelines

� ALWAYS KEEP THE ORIGINAL PICTURE UNTOUCHED IN FILE

� Nature’s guideline: Processing (such as changing brightness and contrast) is appropriate only when it is applied equally across the entire image and is applied equally to controls.

� Wiki: http://wikisites.mcgill.ca/djgroup/index.php/Training:Imaging

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Imaging - McGill University · · 2009-07-10What Is A Digital Image? Digital Image: An image is a...

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