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EC2029 Digital Image Processing Hand Written Lecture Notes - Raji Edition
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Digital image Processing Premium Lecture Notes, Prepared by Raji. Specially for Electronics and Communication Engineering. Syllabus Covered based on Anna University B.E Electronics and Communication Engineering

UNIT-1 (Pages: 81)
DIGITAL IMAGE FUNDAMENTALS
UNIT-2 (Pages: 16)
IMAGE ENHANCEMENT
UNIT-3 (Pages: 34)
IMAGE RESTORATION
UNIT-4 (Pages: 33)
IMAGE SEGMENTATION
UNIT-5 (Pages: 27)
ERROR FREE COMPENSATION

UNIT-1
DIGITAL IMAGE FUNDAMENTALS
Image
Digital image processing
Image elements
Fundamentals steps in digital image processing
Morphological processing
Segmentation
Representation and description
Elements of visual perception
Choroid
Lens
Distribution in rods and cones in retina
Image formation in the eye
Brightness adaption and description
Match band effect
Elements or components of image processing
Physical device
Digitizer
Specialized image processing hardware
Mass storage
1. Short term storage
2. Online storage
3. Archival storage
Networking
Color models
Intensity
Converting colors from RGB+HIS
Image sampling and quantization
1. Basic concept of sampling
2. Representing digital images
Zooming and shrinkage digital images
Introduction to fourier transform
Discreate fourier transform
Power spectrum
Two dimensional DFT and its inverse
Properties of 2- dimensional fourier transform
Distributing and scaling
Rotational
Periodicity and conjugate symmetrical
Properties of DCT
Inverse transform
Singular value decomposition
Digital Camera

UNIT-2
IMAGE ENHANCEMENT
Histogram equalizer
Image enhancement
1. Spatial domain methods
2. Frequency domain method
Spatial averaging
Median filters
Harmonic mean filter
Colour image enhancement

UNIT-3
IMAGE RESTORATION
A model of the image integration
Linear ,position – invariant degradation
Estimating the degradation
Estimation by experimentation
Estimation by modeling
Inverse filtering
Wiener filtering
Unconstained restoration
Geometric transformation
Spatial transformation
Unconstrained restoration
Constrained filtering
Lagrange multipliers methods
Wiener filtering

UNIT-4
IMAGE SEGMENTATION
Fundamentals
Point, line and edge detection
Edge pixels
Methods designed to detect edge pixels
Point detection
Line detection
Basic formulation
Model of a ramp edge
Horizontal gray level profile
Gradient operators
Direction of gradient rector
Local processing
Edge linking and boundary detection
Global processing using hough transform
Thresholding
Intensity histogram that can be separated by single threshold
Dual threshold
Basic global thresholding

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UNIT-5
ERROR FREE COMPENSATION
Black code
Truncated Huffman
Arithmetic coding
Basic formulation
Huffman coding
Need for data compensation
1. Encoder
2. Decoder
JPEG

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