OUP : Higher Education - DIGITAL IMAGE PROCESSING
Digital Image Processing is a basic textbook designed to cater to the needs of undergraduate engineering students of computer science, information technology, electronics and communication, and electrical engineering. Spread over twelve chapters, the book starts with a discussion of image fundamentals, followed by a brief chapter on digital imaging systems. It then broadly addresses core topics of interest such as image transforms, image enhancement, image compression, image segmentation, and colour image processing. It also provides an overview of popular research domains such as biometrics, stenography, image mining, and content-based retrieval systems.
The book strikes a perfect balance between theoretical and mathematical exposition, with several numerical examples, review questions, numerical exercises, and MATLAB programs. |
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Key Features Adopts algorithmic approach to illustrate image processing Provides simple explanations to topics such as Shannon—Fano coding, morphological gradient, polygonal approximations, shape number, and component labellingIncludes solved numerical examples interspersed throughout the bookContains appendices that discuss the basics of MATLAB programming and ImageJ, and provide information on other public domain image processing softwareIncludes a laboratory manual with simple examples illustrated through MATLAB and augmented through ImageJ, a GUI-based public domain software
In the CDMATLAB programs discussed in the lab manual, with representative input and output imagesSelect images from Chapters 1, 2, 8, 9, 10, and 12 of the book reproduced in colour Additional test images for performing laboratory exercises |
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Readership Undergraduate engineering students of computer science, information technology, electronics and communication, and electrical engineering |
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List of contents
Preface
1. Introduction to Image Processing
2. Digital Imaging System
3. Digital Image Processing Operations
4. Digital Image Transforms
5. Image Enhancement and Restoration
6. Image Compression
7. Image Segmentation
8. Colour Image Processing
9. Image Morphology
10. Image Features Representation and Description
11. Object Recognition
12. Related Topics
Appendix A
Appendix B
Appendix C
Bibliography
Index
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Syllabus of Digital Image Processing Course
ReplyDeleteCP9167 DIGITAL IMAGE PROCESSING
UNIT I FUNDAMENTALS OF IMAGE PROCESSING 9
Introduction – Elements of visual perception, Steps in Image Processing Systems – Image Acquisition – Sampling and Quantization – Pixel Relationships – Colour Fundamentals and Models, File Formats. Introduction to the Mathematical tools.
UNIT II IMAGE ENHANCEMENT AND RESTORATION 9
Spatial Domain Gray level Transformations Histogram Processing Spatial Filtering – Smoothing and Sharpening. Frequency Domain: Filtering in Frequency Domain – DFT, FFT, DCT, Smoothing and Sharpening filters – Homomorphic Filtering., Noise models, Constrained and Unconstrained restoration models.
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UNIT III IMAGE SEGMENTATION AND FEATURE ANALYSIS 9
Detection of Discontinuities – Edge Operators – Edge Linking and Boundary Detection – Thresholding – Region Based Segmentation – Motion Segmentation, Feature Analysis and Extraction.
UNIT IV MULTI RESOLUTION ANALYSIS AND COMPRESSIONS 9
Multi Resolution Analysis: Image Pyramids – Multi resolution expansion – Wavelet Transforms, Fast Wavelet transforms, Wavelet Packets.
Image Compression: Fundamentals – Models – Elements of Information Theory – Error Free Compression – Lossy Compression – Compression Standards – JPEG/MPEG.
UNIT V APPLICATIONS OF IMAGE PROCESSING 9
Representation and Description, Image Recognition- Image Understanding – Image Classification – Video Motion Analysis – Image Fusion – Steganography – Colour Image Processing.
TOTAL = 45
REFERENCES
Digital Image Processing - Dr. S.Sridhar Oxford University Press