Pratt, W. K.
Digital Image Processing 4th ed.
PIKS Scientific Inside
デジタル画像処理 第４版
John Wiley & Sons 2007.2
782 pp. (H) + CD 【在庫有り】
ISBN 0-471-76777-8
15,500円
Contents
Preface / Acknowledgments / PART 1 CONTINUOUS IMAGE CHARACTERIZATION. 1 Continuous Image Mathematical Characterization / 2 Psychophysical Vision Properties / 3 Photometry and Colorimetry / PART 2 DIGITAL IMAGE CHARACTERIZATION. 4 Image Sampling and Reconstruction / 5 Image Quantization / PART 3 DISCRETE TWO-DIMENSIONAL PROCESSING. 6 Discrete Image Mathematical Characterization / 7 Superposition and Convolution / 8 Unitary Transforms / 9 Linear Processing Techniques / PART 4 IMAGE IMPROVEMENT. 10 Image Enhancement / 11 Image Restoration Models / 12 Image Restoration Techniques / 13 Geometrical Image Modification. PART 5 IMAGE ANALYSIS. 14 Morphological Image Processing / 15 Edge Detection / 16 Image Feature Extraction / 17 Image Segmentation / 18 Shape Analysis / 19 Image Detection and Registration / PART 6 IMAGE PROCESSING SOFTWARE. 20 PIKS Image Processing Software / 21 PIKS Image Processing Programming Exercises / Appendix / Bibliography / Index.
* The Fourth Edition of Digital Image Processing provides a complete introduction to the field and includes new information that updates the state of the art. The text offers coverage of new topics and includes interactive computer display imaging examples and computer programming exercises that illustrate the theoretical content of the book. These exercises can be implemented using the Programmer's Imaging Kernel System (PIKS) application program interface included on the accompanying CD. *
Russ, J. C.
The Image Processing Handbook 5th ed.
CRC Press 2006.12
817 pp.(H)
ISBN 0-8493-7254-2
25,000円
Contents
1.Introduction. 2.Acquiring Images. Printing and Storage. 3.Correcting Imaging Defects. 4.Image Enhancement (Processing in the Spatial Domain). 5.Processing images in Frequency Space. 6.Segmentation and Thresholding. 7.Processing Binary Images. 8.Global Image Measurements. 9.Feature-Specific Measurements. 10.Feature Recognition and Classification. 11.3D Image Acquisition. 12.3D Image Visualization. 13.Imaging Surfaces. Index/
* This handbook presents an extensive collection of image processing tools to help computer-based systems users understand methods in packaged software and program additions for applications. With over 600 new and revised figures, this edition expands discussions on deconvolution, extended dynamic range images, and multichannel imaging with new material on principal components analysis. It also includes a new chapter on human vision and additional references and presents the latest technologies for image capture and printing. *
Zoubir, A.M. & Iskander, D.R.
Bootstrap Techniques for Signal Processing
Cambridge University Press 2007.2
231 pp. (P)
ISBN 0-521-03405-1
7,200円
Contents
Now in papaerback edition Preface; Notations; 1. Introduction; 2. The bootstrap principle; 3. Signal detection with the bootstrap; 4. Bootstrap model selection; 5. Real data bootstrap applications; Appendix 1. MATLAB codes for the examples; Apendix 2. Bootstrap MATLAB toolbox; References; Index/
* The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. *
Campisi, P. & Eglozarian, K. ed.
Blind Image Deconvolution
Theory and Applications
CRC Press 2007.5
472 pp. (H)
ISBN 0-8493-7367-0
22,400円
Contents
1.Blind image Deconvolution: Problem Formulation and Existing Approaches. 2.Blind Image Deconvolution using Bussgang Techniques. 3.Applications to Image Deblurring and Texture Synthesis. 4.Blind Multiframe Image Deconvolution Using Anisotropic Spatially Adaptive Filtering for Denoising and Regularization. 5.Bayesian Methods Based on Variational Approximations for Blind Image Deconvolution. 6.Deconvolution of Medical Images from Microscopic to Whole Body Images. 7.Bayesian Estimation of Blur and Noise in Remote Sensing Imaging. 8.Deconvolution and Blind Deconvolution in Astronomy. 9.Multiframe Blind Deconvolution Coupled with Frame Registration and Resolution Enhancement. 10.Blind Reconstruction of Multiframe Imagery Based on Fusion and Classification. 11.Blind Deconvolution and Structured Matrix Computations with Applications to Array Imaging. Index/
* The always increasing demand for enhancing the quality of images for consumer applications-medical or biological imaging, in remote sensing, and for astronomy, to cite only a few-has fueled a resurgence of research into blind deconvolution techniques. Blind Image Deconvolution: Theory and Applications surveys the current state of research and practice as presented by the most recognized experts in the field. This comprehensive treatise discusses Bayesian methods, single- and multi-channel techniques, adaptive and multi-frame methods, and a host of applications to multimedia processing, astronomy, remote sensing imagery, and medical and biological imaging at the whole-body, small-part, and cellular levels. *
Owen, M.
Practical Signal Processing
実践 信号処理
Cambridge University Press 2007.5
346 pp. (H)
ISBN 0-521-85478-4
10,300円
Contents
Preface; Part I. Foundations: 1. Introduction; 2. Sampling; 3. Conversion between analogue and digital; 4. The frequency domain; 5. Filters; 6. Likelihood methods; 7. Numerical considerations; Part II. Applications: 8. Audio; 9. Still images; 10. Moving images; 11. Communications; 12. Implementations; Answers to chapter exercises/
* The principles of signal processing are fundamental to the operation of many everyday devices. This book introduces the basic theory of digital signal processing, with emphasis on real-world applications. Sampling, quantisation, the Fourier transform, filters, Bayesian methods and numerical considerations are covered, then developed to illustrate how they are used in audio, image, and video processing and compression, and in communications. The advantages and disadvantages of different approaches are presented in the context of real-world examples, enabling the reader to choose the best solution to a given problem. With over 200 illustrations and over 130 exercises (including solutions), this book will appeal to practitioners working in signal processing, and undergraduate students of electrical and computer engineering. *
Li, J.P. et al. ed.
Wavelet Active Media Technology and Information Processing(In 2 Volumes)
World Scientific Pub., SGP 2006.8
1212 pp *2 vols set
ISBN 981-270-042-0
27,900円
Proceedings of the International Computer Conference 2006 Chongqing, China 29 - 31 August 2006
Contents
1 Theoretical Research/ 2 Algorithm and Construction/ 3 Image Processing and Signal Processing and Communication/ 4 Multi-Agent and Multi-Model Systems/ 5 Systems and Applications/
* Wavelet analysis has gained recognition as a useful tool for analyzing time-frequency, and is playing an important role in signal and information processing. Wavelet analysis is not only based on a bright new idea, but also on concepts that already existed in various forms in many different fields. The formalization and emergence of this wavelet theory is the result of a multidisciplinary effort that has brought together of varied disciplines. This book captures the essence of the state of the art in wavelet analysis and active media technology. *
Jahromi, O. S.
Multirate Statistical Signal Processing
Signals and Communication Technology
Springer-Verlag 2007.3
220 pp. (H)
ISBN 1-4020-5316-9
18,900円
Contents
1. Introduction. 1.1. Multi-channel multirate signal measurement. 1.2. Multirate statistical signal processing. 1.3. Notation. 2. Background. 2.1. Second-order theory of stationary stochastic processes. 2.2. Statistical inference and information. 2.3. Theory of majorization. 2.4. Inverse problems, ill-posedness and Tikhonov’s theory of regularization. 3. Multirate Spectrum Estimation. 3.1. Introduction. 3.2. Formulating the inference problem. 3.3. The Maximum Entropy principle. 3.4. Solving Problem 2. 3.5. On well-posedness of the Maximum Entropy solution. 3.6. Practical considerations. 3.7. Examples. 3.8. Discussion on the Maximum Entropy formalism. 3.9. Concluding remarks. 4. Multirate Time Delay Estimation. 4.1. Introduction. 4.2. Time-Delay Estimation in Multirate Sensor Arrays. 4.3. Fusion of Low-rate Signals In The Presence Of Time Delay. 4.4. Designing The Synthesis Filters. 4.5. Procedure for designing multirate sensor arrays. 4.6. Concluding Remarks. 4.7. Proof of Theorem 1. 4.8. Proof of Theorem 2. 4.9. Perfect reconstruction linear-phase filter banks. 5. Multirate Signal Estimation. 5.1. Introduction. 5.2. Problem Statement. 5.3. Statistics of the non-observable vector X and the measurement vector V. 5.4. Estimating X given V. 5.5. Discussion. 5.6. Putting everything together. 5.7. Concluding remarks. 6. Algebraic Theory of Scalable Multirate Systems. 6.1. Introduction. 6.2. FIR analysis and synthesis systems. 6.3. Scalability in multirate systems. 6.4. Embedding partial ordering of scalability in a total ordering. 6.5. SC-Optimality and Subband Coding. 6.6. SC-Optimality and the Principal Component Filter Bank. 6.7. Concluding remarks. 6.8. Summary. 7. Information Theory of Multirate Systems. 7.1. Introduction. 7.2. The information content of a low-rate measurement. 7.3. Measuring statistical information in practice. 7.4. Scalability in terms of information. 7.5. Concluding remarks and open problems. 8. Distributed Algorithms. 8.1. Introduction. 8.2. Spectrum estimation using sensor networks. 8.3. Inverse and Ill-posed problems. 8.4. Spectrum estimation using generalized projections. 8.5. Distributed algorithms for calculating generalized projection. 8.6. Concluding remark. 8.7. Acknowledgements. 9. Epilogue. *
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