Fundamentals of Image Processing

Subject code: 181102

Dr. C.H. Vithalani,Government Engineering College,

Rajkot.

1. Digital Image Fundamentals2. Image enhancement in spatial domain3. Filtering in frequency domain4. Image restoration and reconstruction5. Color Image Processing6. Image Compression7. Image Segmentation8. Morphological Image ProcessingLaboratory work:MATLAB or SCILAB (Image and video processing toolbox

and some stand alone programs in C )

Syllabus Overview

1. Digital Image Processing, Rafael C. Gonzalez and Richard E. Woods, Third Edition, Pearson Education

2. Digital Image Processing Using MATLAB, Rafael C. Gonzalez, Richard E. Woods, and Steven L. Eddins, Second Edition, Tata McGraw Hill Publication

3. Digital Image Processing, S Jayaraman, S Esakkirajan, T Veerakumar, Tata McGraw Hill Publication

4. Digital Image Processing, S Sridhar, Oxford University Press.

Books

Topic 1Digital Image Fundamentals

1.1 Introduction of Image Processing1.2 Human Visual System1.3 Image as 2D data 1.4 Image representation: Grey scale and Color1.5 Image Sampling and Quantization

Discussion points

Introduction to Image Processing

• Image may be defined as a two dimensional function f(x,y) where x, y spatial coordinates

• Amplitude f at any point (x,y) is called intensity orgray level at that point

• For 256 level (8 bit) image, black pixel has intensity 0 i.e. f=0 and white pixel has intensity maximum i.e. f=255

• Intermediate gray level pixel has value between 1to 254

• 24 bit color image pixel has three color (RGB) each 8 bit

Sampling and Quantization

Digitizing co-ordinate value is called sampling

Digitizing amplitude value is called quantization

Sampling and Quantization

Quality of image depends on ……

How many samples we are taking

&

How many amplitude levels we are using

• Sampling and quantization process gives matrix of numbers

Image as 2-D data

Number of bits required to store image = M N kk= Number of bits/pixel If number of amplitude levels are L L=2k k=log2(L)

General Image Processing System

ImageSensor Digitizer Computer Display

Printer/Plotter

Memory

Image Processing Scheme

ImageSensing Digitization

Image Enhancement

Image Restoration

Image Segmentation

Image Compression

Memory(Storage)

FeatureExtraction

Introduction to Image Processing

Purpose of digital image processing:• Improvement of pictorial information for

human interpretations• Processing of image data for analysis

purpose• Compression of image data for storage and

transmission• Representation of image for autonomous machine perception.

Machine Vision ApplicationsFor machine vision information is extracted from image:• Product assembly and inspection• Automated target detection and tracking• Finger print recognition• Iris recognition• Processing of aerial and satellite images for

whether prediction, corps assessment etc .

Steps of Image Processing for machine vision applications …

• Image acquisition: Imaging sensor and digitization

• Image PreprocessingEnhance quality and noise removal

• Image SegmentationPartition image into different objects

• Feature selection (extraction)Area of interest for analysis

• Recognition and interpretationAssignment of labels to objects

• What we do while we view a scene ?- Rapid movement of eye between points of fixation - Sampling scene with high resolution fovea- Stitch together high resolution representation of scene

- Initial fixations are predicted by certain image properties

• Video camera does the same thing, It does horizontal and vertical scanning and it takes samples and quantize the points (pixels)

Human Visual System

Human Visual PerceptionPurpose of understanding human visual system:• Help to design compression algorithms• Help to develop image enhancement

algorithms

(The Transmission Path)

(Input Sensor)

Human Visual Perception Lies in the Visible Region (350 to 780 nm) of the EM Spectrum.

LI

Incident Energy DistributionReflectivity /Transmissivityof Object

Light intensity =

Human Visual PerceptionBeautiful sensor given by God to human being …..

Tough Transparent Tissue

Opaque membrane Blood Vessels

Varies in diameterfrom 2 to 8 mm

Blind Spot

Fibrous cells60-70% Water6% Fat, Protein

Video

Retina is innermost membrance of eye. When lens is properly focused, light from outside object imaged on retina• The Retina is Covered with 2 types of Photoreceptors

(light sensitive organs):• RodsRods (75 to 150 millions): Provides brightness sensation• Cones (6 to 7 millions): Provides color sensation

(Broadly three groups: RED, GREEN and BLUE)(Each group of cones are tuned to small band of wavelengths)

Human Visual Perception

Human Visual Perception

Human eye is most sensitive to green color

Human Visual PerceptionAbsence of rods and cones in certain area of retina results into blind spot

Cones(In Fovea)

Rods

Video about human visual perception

Absence of cones means color blindness

• We do not notice or process majority of Visual stimuli….

• That is good otherwise unnecessary data will be accumulate in our brain.

• Our eye do not provide high resolution and highcolor information across the entire field of view

• Center two degrees of visual angle (fovea) provide high resolution, full color information using cones located around fovea

• Around fovea, rods are distributed having lowresolution and Grey scale information

Human Visual System Limitations

Simultaneous ContrastSimultaneous Contrast

Hermann GridHermann Grid(Visual effect due to lateral inhibition)(Visual effect due to lateral inhibition)

Mach Bands EffectMach Bands Effect

Spatial Frequency …..Spatial Frequency …..

• What will be storage requirement of monochrome image forimage size 512x512 pixel ?

• What will be storage requirement for 256 gray-level image for size 1024x768 ?

• What will be storage requirement for the true color image ofsize 1440x900 pixel ?

Exercise

Thank you