Digital image processing system –Fundamental steps in digital image processing, Components of an image processing system, Structure of human eye, Image formation, Brightness adaptation and discrimination. Basic concepts in sampling and Quantization, Representing digital images, Neighbors of a pixel, Adjacency, Connectivity, Regions and Boundaries, Distance Measures, A simple image formation mode. Image transforms - Properties of 2D DFT, Discrete Cosine Transform, SVD transform, Wavelet transform.

Image Enhancement: Histogram Processing- Histogram equalization, Matching, Local Histogram Processing, histogram statistics for image enhancement, smoothing linear filters, sharpening spatial filters. Image Restoration: A model of image degradation/ restoration process, Noise models–Inverse filtering – Wiener filtering – Constrained least mean square filtering – Geometric transformation.

Image Compression: Need for compression – Huffman Coding, Arithmetic Coding, Run length coding, Lossy compression - Transform coding, Wavelet coding. Image segmentation: Detection of isolated points, line detection, Edge models, Basic edge detection, Region based segmentation – region growing, Region splitting and merging.

Basic concept, Dilation and Erosion process for binary and gray image with applications, Opening & Closing for binary and gray image with applications, Hit-or-Miss Transformation, Basic Morphological Algorithms, Morphological reconstruction.

Introduction to computer vision- Image formation and Processing: Geometric primitives and transformations; Photometric image formation; The digital camera; Point Operators; Linear Filtering; Neighborhood Operators; Pyramids and Wavelets - Fourier Transforms; Geometric transformations- Applications of CV.