RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPALPROGRAMME: Electronics & Communication EngineeringCOURSE: EC-7102 Digital Image ProcessingCategory of course Course Title Course code Credit-6C Theory paper (ES)DCO(E)-I Digital ImageProcessing EC-7102 L T P Max. Marks-100Min. Marks: 35Duration: 3 hrs.3 1 0Course Contents
Unit-I
Digital Image Processing (DIP)Introduction, examples of fields that use DIP, fundamental Steps in DIP, components of an image processing System.Digital Image Fundamentals: elements of visual perception, image sensing and acquisition, image sampling and quantization, basicrelationships between pixels.
Unit-II
Image TransformsTwo-dimensional (2-D) impulse and its shifting properties, 2-D continuous Fourier Transform pair, 2-D sampling and sampling theorem,2-D Discrete Fourier Transform (DFT), properties of 2-D DFT.Other transforms and their properties: Cosine transform, Sine transform, Walsh transform, Hadamard transform, Haar transform,Slant transform, KL transform.
Unit-III
Image EnhancementSpatial domain methods: basic intensity transformation functions, fundamentals of spatial filtering, smoothing spatial filters (linear andnon-linear), sharpening spatial filters (unsharp masking and highboost filters), combined spatial enhancement method.Frequency domain methods: basics of filtering in frequency domain, image smoothing filters (Butterworth and Guassian low passfilters), image sharpening filters (Butterworth and Guassian high pass filters), selective filtering.
Unit-IV
Image RestorationImage degradation/restoration, noise models, restoration by spatial filtering, noise reduction by frequency domain filtering, linearposition invariant degradations, estimation of degradation function, inverse filtering, Wiener filtering, image reconstruction fromprojection.
Unit-V
Image CompressionFundamentals of data compression: basic compression methods: Huffman coding, Golomb coding, LZW coding, Run-Length coding,Symbol based coding.Digital Image Watermarking, Representation and Description- minimum perimeter polygons algorithm (MPP).
References:
1. R. C. Gonzalez and R. E. Woods: Digital Image Processing, 3rd Edition, Pearson Education.2. A. K. Jain: Fundamentals of Digital Image Processing, PHI Learning.3. S. Annadurai and R. Shanmugalakshmi: Fundamentals of Digital Image Processing, Pearson Education.4. M. Sonka, V. Hlavac and R. Boyle: Digital Image Processing and Computer Vision: Cengage Learning.5. B. Chanda and D. D. Majumder: Digital Image Processing and Analysis, PHI Learning.6. S. Jayaraman, S. Esakkirajan and T. Veerakumar: Digital Image Processing, TMH.
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