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Local approximation techniques in signal and image processing / Vladimir Katkovnik, Karen Egiazarian, and Jaakko Astola

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SPIE press monograph ; 157Publisher: Bellingham, Wash. <1000 20th St. Bellingham WA 98225-6705 USA> : SPIE, 2006Description: 1 online resource (xvii, 553 p. : ill.)ISBN:
  • 9780819478337
  • 0819460923
  • 9780819460929
Subject(s): Additional physical formats: 0819460923. | 9780819460929. | Erscheint auch als: No title Druck-AusgabeDDC classification:
  • 621.3822
  • 621.382/2 22
LOC classification:
  • TK5102.9
DOI: DOI: 10.1117/3.660178Online resources: Additional physical formats: Also available in print version.Summary: This book deals with a wide class of novel and efficient adaptive signal processing techniques developed to restore signals from noisy and degraded observations. These signals include those acquired from still or video cameras, electron microscopes, radar, x rays, or ultrasound devices, and are used for various purposes, including entertainment, medical, business, industrial, military, civil, security, and scientific applications. In many cases useful information and high quality must be extracted from the imaging. However, often raw signals are not directly suitable for this purpose and must be processed in some way. Such processing is called signal reconstruction. This book is devoted to a recent and original approach to signal reconstruction based on combining two independent ideas: local polynomial approximation and the intersection of confidence interval ruleSummary: 1. Introduction -- 1.1. Linear local approximation -- 1.2. Anisotropy -- 1.3. Nonlinear local approximation -- 1.4. Multiresolution analysis -- 1.5. Imaging applications -- 1.6. Overview of the bookSummary: 10. Nonlinear methods -- 10.1. Why nonlinear methods? -- 10.2. Robust M-estimation -- 10.3. LPA-ICI robust M-estimates -- 10.4. Nonlinear transform methodsSummary: 11. Likelihood and quasi-likelihood -- 11.1. Local maximum likelihood -- 11.2. Binary and counting observations -- 11.3. Local quasi-likelihood -- 11.4. Quasi-likelihood LPA-ICI algorithmsSummary: 12. Photon imaging -- 12.1. Direct Poisson observations -- 12.2. Indirect Poisson observations -- 12.3. Local ML Poisson inverse -- 12.4. Computerized tomographySummary: 13. Multiresolution analysis -- 13.1. MR analysis: basic concepts -- 13.2. Nonparametric LPA spectrum -- 13.3. Thresholding -- 13.4. Parallels with waveletsSummary: 14. Appendix -- 14.1. Analytical regular grid kernels -- 14.2. LPA accuracy -- 14.3. ICI rule -- 14.4. Cross validation -- 14.5. Directional LPA accuracy -- 14.6. Random processes -- 14.7. 3D inverse -- 14.8. Nonlinear methods -- References -- IndexSummary: 2. Discrete LPA -- 2.1. Introduction -- 2.2. Basis of LPA -- 2.3. Kernel LPA estimates -- 2.4. Nonparametric regression -- 2.5. Nonparametric interpolationSummary: 3. Shift-invariant LPA kernels -- 3.1. Regular grid kernels -- 3.2. Vanishing moments -- 3.3. Frequency domain -- 3.4. Numerical shift-invariant kernels -- 3.5. Numerical differentiationSummary: 4. Integral LPA -- 4.1. Integral kernel estimators -- 4.2. Analytical kernels -- 4.3. Generalized singular functions -- 4.4. Potential derivative estimatesSummary: 5. Discrete LPA accuracy -- 5.1. Bias and variance of estimates -- 5.2. Ideal scale -- 5.3. Accuracy of potential differentiatorsSummary: 6. Adaptive-scale selection -- 6.1. ICI rule -- 6.2. Multiple-window estimation -- 6.3. Denoising experimentsSummary: 7. Anisotropic LPA -- 7.1. Directional signal processing -- 7.2. Directional LPA -- 7.3. Numerical directional kernelsSummary: 8. Anisotropic LPA-ICI algorithms -- 8.1. Accuracy analysis -- 8.2. Adaptive-scale algorithms -- 8.3. Directional image denoising -- 8.4. Directional differentiation -- 8.5. Shading from depth -- 8.6. Optical flow estimationSummary: 9. Image reconstruction -- 9.1. Image deblurring -- 9.2. LPA-ICI deblurring algorithms -- 9.3. Motion deblurring -- 9.4. Super-resolution imaging -- 9.5. Inverse halftoning -- 9.6. 3D inversePublication frequency: Erscheinungsweise: 1. Introduction -- 1.1. Linear local approximation -- 1.2. Anisotropy -- 1.3. Nonlinear local approximation -- 1.4. Multiresolution analysis -- 1.5. Imaging applications -- 1.6. Overview of the bookPPN: PPN: 101818905XPackage identifier: Produktsigel: ZDB-50-SPI
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