JNTUK B.Tech Image Processing gives you detail information of Image Processing R13 syllabus It will be help full to understand you complete curriculum of the year.
Unit: 1 : Introduction to Image Processing: Overview of Image Processing, Nature of Image Processing, Image Processing Computer Graphics, Signal Processing, Machine Vision, video Processing, Optics, Statistics, Digital Image Representation, Types of Images, Digital Image Processing Operations, Fundamental steps in Image Processing, Image Processing Applications.
Digital Imaging System.
Digital Imaging System: Physical Aspects of Imaging Acquisition, Biological Aspects of Image Acquisition, Properties of Human Visual System, Review of Digital Camera, Sampling and Quantization, Image Quality – Optical Resolution, Image Display Device and Device Resolution, Digital Halftone Process – Random Dithering, Ordered Dithering, Non-Periodic Dithering, Image Storage and File Formats – Need for File Format Types of File Formats – GIF, JPEG, PNG, DICOM, SVG Structure of TIFF File Format.
Unit: 2 : Digital Image Processing Operations: Basic Relationship and Distance Metrics, Classification of Image Processing Operations, Arithmetic and Logical Operations, Geometric Operations, Image Interpolation Techniques, Set Operations, Statistical Operations, Convolution and Correlation Operations, Data Structures and Image Processing Applications Development – Relational Structures, Hierarchical Data Structures, Pyramids, Quadtrees, Application Development.
Digital Image Transforms: Need for Image Transforms, Spatial Frequencies in Image Processing, Introduction to Fourier Transform, Discrete Fourier Transform, Fast Fourier Transform and its algorithm, Properties of Fourier transform – Sampling Theorem, Parseval’s Theorem, Discrete Cosine Transform, Discrete Sine Transform, Walsh Transform, Hadamard Transform, Haar Transform, Slant Transform, SVD and KL Transforms or Hotelling Transform.
Unit: 3 : Image Enhancement: Image Quality and Need for Image Enhancement, Image Quality Metrics, Image Enhancement Point Operations Linear and Non-linear Functions, Piecewise Linear Functions, Histogram-based Techniques, Spatial Filtering Concepts, Image Smoothing Spatial Filters and its design, Image Sharpening Spatial Filters Frequency Domain Filtering.
Image Restoration: Image Degradation (Restoration) Model, Categories of Image Degradations, Noise Modeling, Blur and Distortions, Image Restoration in the Presence of Noise Only, Mean Filters, Order-statistics Filters, Image Restoration Techniques, Constrained and Unconstrained Methods, Geometrical Transforms for Image Restoration.
Unit: 4 : Image Compression: Image Compression Model, Compression Algorithm and its types – Entropy Coding, Predictive Coding, Transform Coding, Layered Coding, Types of Redundancy – Coding Redundancy, Inter-pixel Redundancy, Psychovisual Redundancy, Chromatic Redundancy.
Lossless Compression Algorithms, Run-length Coding, Huffman Coding , Shannon–Fano Coding, Bit-plane Coding, Arithmetic Coding, Lossless Predictive Coding, Lossy Compression Algorithms, Block Transform Coding, Image and Video Compression standards, JPEG,Video Compression – MPEG.
Unit: 5 : Image Segmentation: Introduction – Classification of Image Segmentation Algorithms, Detection of Discontinuities, Edge Detection – Staged in Edge Detection – Types of Edge Detectors, First-order Edge Detection Operators – Second-order Derivative Filters, Edge Operator Performance, Edge Linking Algorithms, Principle of Thresholding – Effect of Noise over Threshold Process and Peakiness Test – Parametric Methods, Non-parametric Methods, Principle of Region- growing –Dynamic Segmentation approaches , Validation of Segmentation Algorithms.
Unit: 6 : Colour Image Processing: Introduction – Colour Fundamentals, Devices for Colour Imaging, Colour Image Storage and Processing – Colour Models – RGB Colour Model, HIS Colour Model, HSV Colour Model, HLS Colour Model, TV Colour Model YUV Model, YIQ Model, Y Cb Cr Colour Model, Printing Colour Models- CMK and CMYK Models.Colour Quantization – Popularity Algorithm, Median-cut Algorithm, Octree- based Algorithm, Pseudo Colour Image Processing.
Full Colour Processing – Colour Transformation – Image Filters for Colour Images – Noise in Colour Images, Colour Image Segmentation– Thresholding, K-means Clustering Technique, RGB Colour Space Segmentation, Colour Features.
Text Books
- S.Sridhar, “Digital Image Processing” Oxford Publishers, 2011
- S.Jayaraman, S.Esakkirajan, T.Veerakumar, “Digital Image Processing” Mc Graw Hill Publishers, 2009
Reference Books
- Rafael C.Gonzalez and Richard E. Woods, “Digital Image Processing” Pearson Education, 2011. B.Chanda and D. Dutta Majumder, “Digital Image Processing and
- Analysis” Prentice Hall of India, 2011/2012 (Print).
- Anil K. Jain, “Fundamentals of Digital Image Processing,” Prentice Hall of India, 2012.
- Milan Sonka, Hlavac & Boyle “Digital Image Processing and Computer Vision,” Cengage Learning Publishers, 2010 (Reprinted).
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