A Concise Introduction to Image Processing Using C++ (Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series v. 5)
By: Choi-Hong Lai (author), Meiqing Wang (author)Hardback
1 - 2 weeks availability
Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, allowing you to easily apply these techniques in real-world problems. The book presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations (PDEs), and new image compression methods, such as fractal image compression and wavelet compression. It begins with coverage of representation, and then moves on to communications and processing. It concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. The accompanying CD-ROM contains code for all algorithms.
Suitable as a text for any course on image processing, the book can also be used as a self-study resource for researchers who need a concise and clear view of current image processing methods and coding examples. The authors introduce mathematical concepts with rigor suitable for readers with some background in calculus, algebra, geometry, and PDEs. All algorithms described are illustrated with code implementation and many images compare the results of different methods. The inclusion of C++ implementation code for each algorithm described enables students and practitioners to build up their own analysis tool.
Basic Concepts of Images Analogue Signals Digital Signals Grey-Scale Images Colour Images Image Storage Formats Video Exercises References Partial Code Examples Basic Image Processing Tools Correlation Operation and Convolution Operation Fourier Transform The Discrete Cosine Transform The Gabor Transform The Wavelet Transform Further Reading: Orthogonality and Completeness Exercises References Partial Code Examples Preprocessing Techniques for Images Pixel Brightness (Grey-Level) Transformations Concepts and Models of Image Preprocessing Image Smoothing Image Enhancement Image Restoration Processing Methods Using Partial Differential Equations Further Reading Exercises References Partial Code Examples Image Segmentation Thresholding Edge-Based Segmentation Region-Based Segmentation Further Reading Exercises References Partial Code Examples Mathematical Morphology Some Basic Concepts of Set Theory Morphology for Binary Images Morphology for Grey-Scale Images Further Reading Exercises References Partial Code Examples Image Compression Image Fidelity Metrics Lossless Compression Lossy Compression Image Compression Standards: JPEG and MPEG Further Reading Exercises References Partial Code Examples Index
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- ID: 9781584888970
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