BIT Image Processing
bitsemester 8
Unit 1:Introduction and Fundamentals
Definition of digital image, pixels, representation of digital image in spatial domain as well as in matrix form, Block diagram of fundamental steps in digital image processing, Elements of Digital Image Processing systems, Light and EM Spectrum, Image acquisition using a single sensor, Image Acquisition Using Sensor Strips, Image Acquisition process, A simple image formation model, Representing Digital Images, Spatial and Intensity Resolution, Image Interpolation, Neighbors of a Pixel, Adjacency, Connectivity, Regions, and Boundaries
Unit 2:Intensity Transformations and Spatial Filtering
Spatial domain, Transform domain, Spatial Domain Process, Image Negatives, Log Transformations, Power-Law (Gamma) Transformations, Bit-plane Slicing, Histogram Equalization, Histogram Matching, Basics of Spatial Filtering, Spatial Correlation, Spatial Convolution, Linear filters, Spatial Low pass smoothing filters, Averaging, Weighted Averaging, Non-Linear filters, Median filter, Maximum and Minimum filters, High pass sharpening filters, High boost filter, high frequency emphasis filter, Gradient based filters
Unit 3:Filtering in the Frequency Domain
Fourier Series and Fourier Transform, Impulses and the Sifting Property, The Discrete Fourier Transform (DFT) of One Variable, 2-D Fourier Transform, Aliasing in Images, Moiré patterns, Properties of the 2-D DFT, Zero Padding, Zero-Phase-Shift Filters, Image Smoothing Using Filter Domain Filters, Image Sharpening Using Frequency Domain Filters, Computing and Visualizing the 2D DFT (Time Complexity of DFT), Derivation of 1-D Fast Fourier Transform, Time Complexity of FFT, Concept of Convolution, Correlation and Padding, Hadamard transform, Haar transform and Discrete Cosine transform
Unit 4:Image Restoration & Reconstruction
A Model of Image Degradation/Restoration Process, Noise Sources, Range Imaging, Noise Models, Mean Filters: Arithmetic, Geometric, Harmonic and Contraharmonic Mean Filters, Order Statistics Filters: Median, Min and Max, Midpoint and Alpha Trimmed Mean Filters, Band Pass and Band Reject Filters: Ideal, Butterworth and Gaussian Band Pass and Band Reject Filters; Introduction, Definition of Compression Ratio, Relative Data Redundancy, Average Length of Code, Redundancies in Image: Coding Redundancy (Huffman Coding), Interpixel Redundancy (Run Length Coding), and Psychovisual Redundancy (4-bit Improved Gray Scale Coding: IGS Coding Scheme)
Unit 5:Introduction to Morphological Image Processing
Logic Operations involving binary images, Introduction to Morphological Image Processing, Definition of Fit and Hit, Dilation and Erosion, Opening and Closing
Unit 6:Image Segmentation
Definition, Similarity and Discontinuity Based Techniques, Point Detection, Line Detection, Edge Detection Using Gradient and Laplacian Filters, Mexican Hat Filters, Edge Linking and Boundary Detection, Hough Transform; Thresholding: Global, Local and Adaptive; Region Based Segmentation: Region Growing Algorithm, Region Split and Merge Algorithm
Unit 7:Wavelet Transform
Fourier vs. Wavelet, Shifting, Five Steps to a Continuous Wavelet Transform, Coefficient Plots, Wavelet Synthesis
