EC2029 Digital Image Processing Hand Written Lecture Notes - Raji Edition

  • 8Jan
  • 2016
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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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