EC 7th sem EC-7102 Digital Image Processing Syllabus RGTU/RGPV 7th semester Syllabus

RGTU/RGPV EC-7102 Digital Image Processing Syllabus
RGTU/RGPV Digital Image Processing SYLLABUS
Electronics and Communication Engineering EC 7th Semester Syllabus


  EC-7102 Digital Image Processing Course Content:

 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, basic relationships between pixels.

Unit-II : Image Transforms
Two-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 Enhancement
Spatial domain methods: basic intensity transformation functions, fundamentals of spatial filtering, smoothing spatial filters (linear and non-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 pass filters), image sharpening filters (Butterworth and Guassian high pass filters), selective filtering.

Unit-IV : Image Restoration
Image degradation/restoration, noise models, restoration by spatial filtering, noise reduction by frequency domain filtering, linear position invariant degradations, estimation of degradation function, inverse filtering, Wiener filtering, image reconstruction from projection.

Unit-V : Image Compression
Fundamentals 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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