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Course Detail

Course Name Principles of Digital Image Processing
Course Code 15CSE363
Program B. Tech. in Computer Science and Engineering
Year Taught 2019


Unit 1

Mathematical Background for Image Processing: Review of Vectors and Matrices – Review of Probability and statistics. Digital Image Fundamentals: Elements of Visual Perception – Image Sensing and Acquisition – Image Sampling and Quantization – Basic Relationships between Pixels – Image interpolation. Intensity Transformations and Spatial Filtering: Basic Intensity transformation Functions – Histogram Processing – Fundamentals of Spatial Filtering – Smoothing and Sharpening Spatial Filters.

Unit 2

Filtering in Frequency Domain: 2D Discrete Fourier Transforms – Basics of filtering – Image Smoothing and Image Sharpening Using Frequency Domain Filters – Selective Filtering, Image Restoration: Noise Models – Restoration using Spatial Filters – Periodic Noise Reduction by Frequency Domain Filters.

Unit 3

Morphological Image Processing: Erosion – Dilation – Opening – Closing – Hit-orMiss Transform – Extraction of Connected Components. Image Segmentation: Fundamentals – Point, Line and Edge Detection – Thresholding – Region Based Segmentation – Region Growing – Region Splitting and Merging. Color image processing.

Text Books

  • Gonzalez R C and Woods R E, “Digital Image Processing”, Third Edition, Pearson Education, 2009


  • Pratt W K, “Digital Image Processing”, Fourth Edition, John Wiley & Sons, 2007.
  • Castleman K R, “Digital Image Processing”, Prentice Hall, 1996.
  • Gonzalez, Woods and Eddins, “Digital Image Processing Using MATLAB”, Prentice Hall, 2004.
  • Russ J C, “The Image Processing Handbook”, CRC Press, 2007

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