Introduction: Basics of Image formation, Data types, Image Digitization, Sampling, Quantization, Digital Image Properties, Image metrics, Topological Properties of Digital Images, Image Quality, Noise in Images.

 

Image Smoothing and Spatial Filtering: Logarithmic and Contrast-Stretching, Transformations, Histogram Processing. Histogram Equalization, Spatial Filtering, Linear         Spatial Filtering, Averaging, Min/Max, Median

Filtering, Nonlinear Spatial Filtering, Analysis of Filtered images.

 

Frequency Domain Processing: 2-D Discrete Fourier Transform, Computing and Visualizing the 2-D DFT in MATLAB, Filtering in the Frequency Domain, Fundamental Concepts, Basic Steps in DFT Filtering, Obtaining Frequency domain Filters from  Spatial Filters, Lowpass Frequency Domain Filters.

 

Image Restoration: Adding noise, Generating Spatial Random Noise with a Specified Distribution, Periodic Noise, Estimating Noise Parameters, Restoration in the Presence of Noise Only-Spatial Filtering, Spatial Noise Filters, Adaptive Spatial Filters, Periodic Noise Reduction by Frequency Domain Filtering, Modelling the Degradation Function, Direct Inverse Filtering, Wiener Filtering, Blind De-convolution, Geometric Transformations and Image Registration.

 

Image Compression: Coding Redundancy: Huffman Codes, Huffman Encoding, Huffman Decoding, Inter-pixel Redundancy, Psychovisual Redundancy, JPEG Compression: JPEG, JPEG 2000, Analysis techniques for image compression.

 

Morphological Image Processing: Basic Concepts from Set Theory, Binary Images, Dilation and Erosion, The Strel Function, Lookup Tables, Labeling Connected Components, Morphological Reconstruction- Opening by Reconstruction, Filling Holes, Cleaning Border Objects, Gray-Scale Morphology, Dilation and Erosion, Opening and Closing, Reconstruction.

 

Image Segmentation: Point, Line, and Edge Detection, Hough Transform, Global and Local Thresholding. Region-Based Segmentation, Basic Formulation, Region Growing, Region Splitting and Merging, Segmentation Using the Watershed Transform, Watershed Segmentation Using the Distance Transform, Using Gradients, Introduction to Active Contours. Use of Segmentation in Image Analysis.

 

Recommended Books

1. Gonzalez, R.C.,and Woods, R. E., Digital Image Processing Using MATLAB, Pearson (2008) 3^rd ed.
2. Jain, A.K., Digital Image Processing, Dorling Kingsley (2008).
3. Sonka, M., Image Processing, Analysis, and Machine Vision, Cengage (2007) 3^rd ed.