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...
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| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Bellingham, Washington (1000 20th St. Bellingham WA 98225-6705 USA) :
SPIE,
2020.
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| Series: | SPIE Press monograph ;
PM315. |
| Subjects: | |
| ISBN: | 9781510633841 1510633847 9781510633834 1510633839 9781510633858 1510633855 9781510633865 1510633863 |
| Physical Description: | 1 online resource (214 pages) |
Cover
Table of contents
| LEADER | 07020cam a2200541Mi 4500 | ||
|---|---|---|---|
| 001 | kn-on1139240737 | ||
| 003 | OCoLC | ||
| 005 | 20240717213016.0 | ||
| 006 | m o d | ||
| 007 | cr cn||||||||| | ||
| 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 |d COA |d OCLCL | ||
| 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 | |
| 024 | 8 | |a (WaSeSS)ssj0002296092 | |
| 035 | |a (OCoLC)1139240737 |z (OCoLC)1340092055 | ||
| 100 | 1 | |a I︠A︡roslavskiĭ, L. P. |q (Leonid Pinkhusovich), |e author. |1 https://id.oclc.org/worldcat/entity/E39PCjK6MMHJdjY7BbKWvMrQFX | |
| 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. | |
| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
| 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 Knovel (All titles) | ||
| 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. | |
| 655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
| 655 | 9 | |a electronic books |2 eczenas | |
| 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://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpASTT0002/advances-in-sampling?kpromoter=marc |y Full text |
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