The Essential Guide to Image ProcessingAlan C. Bovik Academic Press, 8 de jul. de 2009 - 672 páginas - A complete introduction to the basic and intermediate concepts of image processing from the leading people in the field - Up-to-date content, including statistical modeling of natural, anistropic diffusion, image quality and the latest developments in JPEG 2000 This comprehensive and state-of-the art approach to image processing gives engineers and students a thorough introduction, and includes full coverage of key applications: image watermarking, fingerprint recognition, face recognition and iris recognition and medical imaging. "This book combines basic image processing techniques with some of the most advanced procedures. Introductory chapters dedicated to general principles are presented alongside detailed application-orientated ones. As a result it is suitably adapted for different classes of readers, ranging from Master to PhD students and beyond." – Prof. Jean-Philippe Thiran, EPFL, Lausanne, Switzerland "Al Bovik's compendium proceeds systematically from fundamentals to today's research frontiers. Professor Bovik, himself a highly respected leader in the field, has invited an all-star team of contributors. Students, researchers, and practitioners of image processing alike should benefit from the Essential Guide." – Prof. Bernd Girod, Stanford University, USA "This book is informative, easy to read with plenty of examples, and allows great flexibility in tailoring a course on image processing or analysis." – Prof. Pamela Cosman, University of California, San Diego, USA - A complete and modern introduction to the basic and intermediate concepts of image processing – edited and written by the leading people in the field - An essential reference for all types of engineers working on image processing applications - Up-to-date content, including statistical modelling of natural, anisotropic diffusion, image quality and the latest developments in JPEG 2000 |
Conteúdo
1 | |
23 | |
43 | |
69 | |
Chapter 5 Basic Tools for Image Fourier Analysis | 97 |
Chapter 6 Multiscale Image Decompositions and Wavelets | 123 |
Chapter 7 Image Noise Models | 143 |
Chapter 8 Color and Multispectral Image Representation and Display | 169 |
Chapter 16 Lossless Image Compression | 385 |
Chapter 17 JPEG and JPEG2000 | 421 |
Chapter 18 Wavelet Image Compression | 463 |
Chapter 19 Gradient and Laplacian Edge Detection | 495 |
Chapter 20 Diffusion Partial Differential Equations for Edge Detection | 525 |
Chapter 21 Image Quality Assessment | 553 |
Techniques and Applications | 597 |
Chapter 23 Fingerprint Recognition | 649 |
Chapter 9 Capturing Visual Image Properties with Probabilistic Models | 205 |
Chapter 10 Basic Linear Filtering with Application to Image Enhancement | 225 |
Chapter 11 Multiscale Denoising of Photographic Images | 241 |
Chapter 12 Nonlinear Filtering for Image Analysis and Enhancement | 263 |
Chapter 13 Morphological Filtering | 293 |
Chapter 14 Basic Methods for Image Restoration and Identification | 323 |
Chapter 15 Iterative Image Restoration | 349 |
Chapter 24 Unconstrained Face Recognition from a Single Image | 677 |
Chapter 25 How Iris Recognition Works | 715 |
Chapter 26 Computed Tomography | 741 |
Chapter 27 ComputerAssisted Microscopy | 777 |
Chapter 28 Towards Video Processing | 833 |
835 | |
Outras edições - Ver todos
Termos e frases comuns
algorithm analysis anisotropic anisotropic diffusion applications approach arithmetic coding binary image blur camera chapter codeword coefficients color components computed convolution corresponding decoding decomposition defined denoising detector digital image discrete distortion distribution domain edge detection embedding encoded entropy estimate example face recognition FIGURE filter fingerprint frequency function Gaussian gradient gray level grayscale histogram host signal Huffman coding IEEE IEEE Trans illumination image coding image compression image denoising image f image processing image quality image restoration impulse response input integral iteration JPEG LabVIEW Laplacian linear lossless magnitude masking matrix median methods microscopy morphological noise nonlinear objects operations optimal original image output parameters perceptual performance pixel problem Proc PSNR quantization reconstruction regions representation result samples scale scan Section shown in Fig Signal Process smoother smoothing spatial SPIHT SSIM standard statistical subband symbol techniques threshold values variance vector visual watermark wavelet zero