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Advances in sampling theory and techniques /
"This book presents the current state of the art of digital engineering, as well as recent proposals for optimal methods of signal and image non-redundant sampling and interpolation-error-free resampling. Topics include classical sampling theory, conventional sampling, the peculiarities of samp...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Bellingham, Washington (1000 20th St. Bellingham WA 98225-6705 USA) :
SPIE,
2020.
|
| Colección: | SPIE Press monograph ;
PM315. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mi 4500 | ||
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| 003 | OCoLC | ||
| 005 | 20231027140348.0 | ||
| 006 | m eo d | ||
| 007 | cr bn||||m|||a | ||
| 008 | 200128s2020 wau ob 001 0 eng d | ||
| 040 | |a SPIES |b eng |e rda |c SPIES |d OCLCO |d OCLCF |d UIU |d UPM |d OCLCQ |d YDX |d EUN |d OCLCO |d OCLCQ |d OCLCO | ||
| 020 | |a 9781510633841 |q (pdf) | ||
| 020 | |a 1510633847 |q (pdf) | ||
| 020 | |z 9781510633834 |q (paperback) | ||
| 020 | |z 1510633839 |q (paperback) | ||
| 020 | |z 9781510633858 |q (epub) | ||
| 020 | |z 1510633855 |q (epub) | ||
| 020 | |z 9781510633865 |q (kindle edition) | ||
| 020 | |z 1510633863 |q (kindle edition) | ||
| 024 | 7 | |a 10.1117/3.2554039 |2 doi | |
| 029 | 1 | |a AU@ |b 000068158564 | |
| 029 | 1 | |a AU@ |b 000067251408 | |
| 035 | |a (OCoLC)1139240737 | ||
| 050 | 4 | |a TK5102.9 |b .I225 2020eb | |
| 082 | 0 | 4 | |a 621.382/20151952 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a I͡Aroslavskiĭ, L. P. |q (Leonid Pinkhusovich), |e author. | |
| 245 | 1 | 0 | |a Advances in sampling theory and techniques / |c L. Yaroslavsky. |
| 264 | 1 | |a Bellingham, Washington (1000 20th St. Bellingham WA 98225-6705 USA) : |b SPIE, |c 2020. | |
| 300 | |a 1 online resource (214 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a SPIE Press monograph ; |v PM315 | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface -- 1. Introduction: 1.1. A historical perspective of sampling: from ancient mosaics to computational imaging; 1.2. Book overview -- Part I: Signal sampling: 2. Sampling theorems: 2.1. Kotelnikov-Shannon sampling theorem: sampling band-limited 1D signals; 2.2. Sampling 1D band-pass signals; 2.3. Sampling band-limited 2D signals; optimal regular sampling lattices; 2.4. Sampling real signals; signal reconstruction distortions due to spectral aliasing; 2.5. The sampling theorem in a realistic reformulation; 2.6. Image sampling with a minimal sampling rate by means of image sub-band decomposition; 2.7. The discrete sampling theorem and its generalization to continuous signals; 2.8. Exercises -- 3. Compressed sensing demystified: 3.1. Redundancy of regular image sampling and image spectra sparsity; 3.2. Compressed sensing: why and how it is possible to precisely reconstruct signals sampled with aliasing; 3.3. Compressed sensing and the problem of minimizing the signal sampling rate; 3.4. Exercise -- 4. Image sampling and reconstruction with sampling rates close to the theoretical minimum: 4.1. The ASBSR method of image sampling and reconstruction; 4.2. Experimental verification of the method; 4.3. Some practical issues; 4.4. Other possible applications of the ASBSR method of image sampling and reconstruction; 4.5. Exercises | |
| 505 | 8 | |a 5. Signal and image resampling, and building their continuous models: 5.1. Signal/image resampling as an interpolation problem; convolutional interpolators; 5.2. Discrete sinc interpolation: a gold standard for signal resampling; 5.3. Fast algorithms of discrete sinc interpolation and their applications; 5.4. Discrete sinc interpolation versus other interpolation methods: performance comparison; 5.5. Exercises -- 6. Discrete sinc interpolation in other applications and implementations: 6.1. Precise numerical differentiation and integration of sampled signals; 6.2. Local ("elastic") image resampling: sliding-window discrete sinc interpolation algorithms; 6.3. Image data resampling for image reconstruction from projections; 6.4. Exercises -- 7. The discrete uncertainty principle, sinc-lets, and other peculiar properties of sampled signals: 7.1. The discrete uncertainty principle; 7.2. Sinc-lets: Sharply-band-limited basis functions with Sharply limited support; 7.3. Exercises -- Part II: Discrete representation of signal transformations: 8. Basic principles of discrete representation of signal transformations -- 9. Discrete representation of the convolution integral: 9.1. Discrete convolution; 9.2. Point spread functions and frequency responses of digital filters; 9.3. Treatment of signal borders in digital convolution | |
| 505 | 8 | |a 10. Discrete representation of the Fourier integral transform: 10.1. 1D discrete Fourier transforms; 10.2. 2D discrete Fourier transforms; 10.3. Discrete cosine transform; 10.4. Boundary-effect-free signal convolution in the DCT domain; 10.5. DFT and discrete frequency responses of digital filters; 10.6. Exercises -- Appendix 1. Fourier series, integral fourier transform, and delta function: A1.1. 1D Fourier series; A1.2. 2D Fourier series; A1.3. 1D integral Fourier transform; A1.4. 2D integral Fourier transform; A1.5. Delta function, sinc function, and the ideal low-pass filter; A1.6. Poisson summation formula -- Appendix 2. Discrete Fourier transforms and their properties: A2.1. Invertibility of discrete Fourier transforms and the discrete sinc function; A2.2. The Parseval's relation for the DFT; A2.3. Cyclicity of the DFT; A2.4. Shift theorem; A2.5. Convolution theorem; A2.6. Symmetry properties; A2.7. SDFT spectra of sinusoidal signals; A2.8. Mutual correspondence between the indices of ShDFT spectral coefficients and signal frequencies; A2.9. DFT spectra of sparse signals and spectral zero-padding; A2.10. Invertibility of the shifted DFT and signal resampling; A2.11. DFT as a spectrum analyzer; A2.12. Quasi-continuous spectral analysis; A2.13. Signal resizing and rotation capability of the rotated scaled DFT; A2.14. Rotated and scaled DFT as digital convolution -- References -- Index. | |
| 520 | |a "This book presents the current state of the art of digital engineering, as well as recent proposals for optimal methods of signal and image non-redundant sampling and interpolation-error-free resampling. Topics include classical sampling theory, conventional sampling, the peculiarities of sampling 2D signals, artifacts, compressed sensing, fast algorithms, the discrete uncertainty principle, and sharply-band-limited discrete signals and basis functions with sharply limited support. Exercises based in MATLAB supplement the text throughout"-- |c Provided by publisher | ||
| 500 | |a Title from PDF title page (SPIE eBooks Website, viewed 2020-01-28). | ||
| 590 | |a Knovel |b ACADEMIC - Electronics & Semiconductors | ||
| 650 | 0 | |a Signal processing |x Digital techniques |x Mathematics. | |
| 650 | 0 | |a Image processing |x Digital techniques |x Mathematics. | |
| 650 | 0 | |a Fourier transformations. | |
| 650 | 6 | |a Traitement du signal |x Techniques numériques |x Mathématiques. | |
| 650 | 6 | |a Traitement d'images |x Techniques numériques |x Mathématiques. | |
| 650 | 7 | |a Fourier transformations |2 fast | |
| 650 | 7 | |a Image processing |x Digital techniques |x Mathematics |2 fast | |
| 650 | 7 | |a Signal processing |x Digital techniques |x Mathematics |2 fast | |
| 710 | 2 | |a Society of Photo-Optical Instrumentation Engineers, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 1510633839 |z 9781510633834 |w (DLC) 2019042348 |
| 830 | 0 | |a SPIE Press monograph ; |v PM315. | |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpASTT0002/toc |z Texto completo |
| 938 | |a YBP Library Services |b YANK |n 17220296 | ||
| 938 | |a Society of Photo-Optical Instrumentation Engineers |b SPIE |n 9781510633841 | ||
| 994 | |a 92 |b IZTAP | ||