Image processing and analysis : variational, PDE, wavelet, and stochastic methods
- Chan, Tony F.
- Philadelphia : Society for Industrial and Applied Mathematics, c2005.
- Physical description
- xxi, 400 p. : ill. ; 26 cm.
TA1637 .C4775 2005
- Unknown TA1637 .C4775 2005
- Shen, Jianhong, 1971-
- Includes bibliographical references (p. 373-392) and index.
- Preface-- 1. Introduction-- 2. Some modern image analysis tools-- 3. Image modeling and representation-- 4. Image denoising-- 5. Image deblurring-- 6. Image inpainting-- 7. Image processing: segmentation-- Bibliography-- Index.
- (source: Nielsen Book Data)
- Publisher's Summary
- This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.
(source: Nielsen Book Data)
- Supplemental links
Table of contents only
- Publication date
- Tony F. Chan, Jianhong (Jackie) Shen.