Digital Image Processing

UNIT-I 

INTRODUCTION TO IMAGE PROCESSING: Introduction to images and its processing, Components of image processing systems, image representations, Image file formats, recent applications of digital image processing, image sampling and quantization, Image Analysis, Intensity transformations, contrast stretching, Correlation and convolution, Smoothing filters, sharpening filters, gradient and Laplacian. Need for transform, Fourier, Cosine transforms, 2D Wavelet transform, Different properties of image transform techniques.

UNIT II 

Concept of image compression: Concept of Image compression, lossless techniques (Huffman Coding, Arithmetic and Lempel-Ziv Coding, Other Coding Techniques) and lossy compression techniques (Transform Coding & K-L Transforms, Discrete Cosine Transforms, and BTC), Enhancement in spatial and transform domain, histogram equalization, Directional Smoothing, Median, Geometric mean, Harmonic mean, Homo-morphic filtering

UNIT III 

Image degradation: Image degradation, Type of image blur, Classification of image restoration techniques, image restoration model, Linear and nonlinear restoration techniques, Image denoising, Median filtering. Classification of image segmentation techniques: Boundary detection-based techniques, Point, line detection, Edge detection, Edge linking, local processing, regional processing, Thresholding, Iterative thresholding, Otsu's method, Region-based segmentation, Watershed algorithm, Use of motion in segmentation

UNIT IV

Binarization and Basic Set theory: Binarization, Basic Set theory, Binary morphological operations and its properties, Color Image Representation, Converting Between Color Spaces, The Basics of Color Image Processing, Color Transformations, Spatial Filtering of Color Images, Working Directly in RGB Vector Space, Applications of digital image processing: Case studies.