Image Processing (Elective-II)

Unit I

Digital Image Fundamentals: Steps in Digital Image Processing, Components, Elements of Visual Perception, Image Sensing and Acquisition, Image Sampling and Quantization, Relationships between Pixels, Color Image Fundamentals — RGB, HSI Models, Two-Dimensional Mathematical Preliminaries, 2D Transforms — DFT, DCT.

Unit II

Image Enhancement: Spatial Domain — Gray Level Transformations, Histogram Processing, Basics of Spatial Filtering, Smoothing and Sharpening Spatial Filtering. Frequency Domain — Introduction to Fourier Transform, Smoothing and Sharpening Frequency Domain Filters — Ideal, Butterworth and Gaussian Filters, Homomorphic Filtering, Color Image Enhancement.

Unit III

Image Restoration: Degradation Model, Properties, Noise Models, Mean Filters, Order Statistics, Adaptive Filters, Band Reject Filters, Band Pass Filters, Notch Filters, Optimum Notch Filtering, Inverse Filtering, Wiener Filtering.

Unit IV

Image Segmentation: Edge Detection, Edge Linking via Hough Transform, Thresholding, Region-Based Segmentation — Region Growing, Region Splitting and Merging, Morphological Processing — Erosion and Dilation, Segmentation by Morphological Watersheds — Dam Construction, Watershed Segmentation Algorithm.

Unit V

Image Compression and Recognition: Need for Data Compression, Huffman, Run Length Encoding, Shift Codes, Arithmetic Coding, JPEG Standard, MPEG. Boundary Representation and Description, Fourier Descriptor, Regional Descriptors — Topological Features, Texture, Patterns and Pattern Classes, Recognition Based on Matching.