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Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets

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Personen und Körperschaften: Haddad, Paul R. (VerfasserIn), Akansu, Ali N (MitwirkendeR)
Titel: Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
Format: E-Book
Sprache: Englisch
veröffentlicht:
Burlington Elsevier Science 1992
Schlagwörter:
Signal processing > Digital techniques
Coding theory
Signal processing ; Digital techniques
Quelle: Verbunddaten SWB
Zugangsinformationen: Elektronischer Volltext - Campuslizenz
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520 |a This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decompos. 
520 |a 4.6 LeGall-Tabatabai PR Filter Bank4.7 Princen-Bradley QMF; 4.8 Optimal PR-QMF Design for Subband Image Coding; 4.9 Performance of PR-QMF Families; 4.10 Aliasing Energy in Multiresolution Decomposition; 4.11 Time and Frequency Localizations; 4.12 GTC and NER Performance; 4.13 Summary; Chapter 5. Wavelet Transform; 5.1 Time-Frequency Decompositions; 5.2 The Short-Time Fourier Transform; 5.3 The Wavelet Transform; 5.4 Multiresolution Signal Decomposition; 5.5 Wavelet Regularity and Wavelet Families; 5.6 Biorthogonal Wavelets and Filter Banks; 5.7 Discussions and Conclusion; 5.8 Epilogue 
520 |a Appendix A: Resolution of the Identity and InversionAppendix B: Orthonormality in Frequency; Appendix C: Problems; Index 
520 |a Chapter 3. Theory of Subband Decomposition3.1 Multirate Signal Processing; 3.2 Bandpass and Modulated Signals; 3.3 Mth Band, Mirror, and Power Complementary Filters; 3.4 Two-Channel Filter Banks; 3.5 M-Band Filter Banks; 3.6 Cascaded Lattice Structures; 3.7 IIR Subband Filter Banks; 3.8 Two-Dimensional Subband Decomposition; 3.9 Quantization Effects in Filter Banks; 3.10 Summary; Chapter 4. Filterbank Families: Design and Performance; 4.1 Binomial QMF-Wavelet Filters; 4.2 Maximally Flat Filters; 4.3 Bernstein QMF-Wavelet Filters; 4.4 Johnston QMF Family; 4.5 Smith-Barnwell PR-CQF Family 
520 |a Front Cover; Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets; Copyright Page; Table of Contents; Preface; Chapter 1. Introduction; 1.1 Introduction; 1.2 Why Signal Decomposition?; 1.3 Decompositions: Transforms, Subbands, and Wavelets; 1.4 Performance Evaluation; Chapter 2. Orthogonal Transforms; 2.1 Signal Expansions in Orthogonal Functions; 2.2 Transform Efficiency and Coding Performance; 2.3 Fixed Transforms; 2.4 Parametric Modeling of Signal Sources; 2.5 Lapped Orthogonal Transforms; 2.6 2D Transform Implementation; 2.7 Summary 
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contents This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decompos., 4.6 LeGall-Tabatabai PR Filter Bank4.7 Princen-Bradley QMF; 4.8 Optimal PR-QMF Design for Subband Image Coding; 4.9 Performance of PR-QMF Families; 4.10 Aliasing Energy in Multiresolution Decomposition; 4.11 Time and Frequency Localizations; 4.12 GTC and NER Performance; 4.13 Summary; Chapter 5. Wavelet Transform; 5.1 Time-Frequency Decompositions; 5.2 The Short-Time Fourier Transform; 5.3 The Wavelet Transform; 5.4 Multiresolution Signal Decomposition; 5.5 Wavelet Regularity and Wavelet Families; 5.6 Biorthogonal Wavelets and Filter Banks; 5.7 Discussions and Conclusion; 5.8 Epilogue, Appendix A: Resolution of the Identity and InversionAppendix B: Orthonormality in Frequency; Appendix C: Problems; Index, Chapter 3. Theory of Subband Decomposition3.1 Multirate Signal Processing; 3.2 Bandpass and Modulated Signals; 3.3 Mth Band, Mirror, and Power Complementary Filters; 3.4 Two-Channel Filter Banks; 3.5 M-Band Filter Banks; 3.6 Cascaded Lattice Structures; 3.7 IIR Subband Filter Banks; 3.8 Two-Dimensional Subband Decomposition; 3.9 Quantization Effects in Filter Banks; 3.10 Summary; Chapter 4. Filterbank Families: Design and Performance; 4.1 Binomial QMF-Wavelet Filters; 4.2 Maximally Flat Filters; 4.3 Bernstein QMF-Wavelet Filters; 4.4 Johnston QMF Family; 4.5 Smith-Barnwell PR-CQF Family, Front Cover; Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets; Copyright Page; Table of Contents; Preface; Chapter 1. Introduction; 1.1 Introduction; 1.2 Why Signal Decomposition?; 1.3 Decompositions: Transforms, Subbands, and Wavelets; 1.4 Performance Evaluation; Chapter 2. Orthogonal Transforms; 2.1 Signal Expansions in Orthogonal Functions; 2.2 Transform Efficiency and Coding Performance; 2.3 Fixed Transforms; 2.4 Parametric Modeling of Signal Sources; 2.5 Lapped Orthogonal Transforms; 2.6 2D Transform Implementation; 2.7 Summary
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spelling Haddad, Paul R. VerfasserIn (DE-627)1236113616 (DE-576)166113611 aut, Multiresolution Signal Decomposition Transforms, Subbands, and Wavelets, Burlington Elsevier Science 1992, 1 online resource (389 pages), Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Print version record, This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decompos., 4.6 LeGall-Tabatabai PR Filter Bank4.7 Princen-Bradley QMF; 4.8 Optimal PR-QMF Design for Subband Image Coding; 4.9 Performance of PR-QMF Families; 4.10 Aliasing Energy in Multiresolution Decomposition; 4.11 Time and Frequency Localizations; 4.12 GTC and NER Performance; 4.13 Summary; Chapter 5. Wavelet Transform; 5.1 Time-Frequency Decompositions; 5.2 The Short-Time Fourier Transform; 5.3 The Wavelet Transform; 5.4 Multiresolution Signal Decomposition; 5.5 Wavelet Regularity and Wavelet Families; 5.6 Biorthogonal Wavelets and Filter Banks; 5.7 Discussions and Conclusion; 5.8 Epilogue, Appendix A: Resolution of the Identity and InversionAppendix B: Orthonormality in Frequency; Appendix C: Problems; Index, Chapter 3. Theory of Subband Decomposition3.1 Multirate Signal Processing; 3.2 Bandpass and Modulated Signals; 3.3 Mth Band, Mirror, and Power Complementary Filters; 3.4 Two-Channel Filter Banks; 3.5 M-Band Filter Banks; 3.6 Cascaded Lattice Structures; 3.7 IIR Subband Filter Banks; 3.8 Two-Dimensional Subband Decomposition; 3.9 Quantization Effects in Filter Banks; 3.10 Summary; Chapter 4. Filterbank Families: Design and Performance; 4.1 Binomial QMF-Wavelet Filters; 4.2 Maximally Flat Filters; 4.3 Bernstein QMF-Wavelet Filters; 4.4 Johnston QMF Family; 4.5 Smith-Barnwell PR-CQF Family, Front Cover; Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets; Copyright Page; Table of Contents; Preface; Chapter 1. Introduction; 1.1 Introduction; 1.2 Why Signal Decomposition?; 1.3 Decompositions: Transforms, Subbands, and Wavelets; 1.4 Performance Evaluation; Chapter 2. Orthogonal Transforms; 2.1 Signal Expansions in Orthogonal Functions; 2.2 Transform Efficiency and Coding Performance; 2.3 Fixed Transforms; 2.4 Parametric Modeling of Signal Sources; 2.5 Lapped Orthogonal Transforms; 2.6 2D Transform Implementation; 2.7 Summary, Signal processing Digital techniques, Coding theory, Signal processing ; Digital techniques, Akansu, Ali N MitwirkendeR ctb, 9780120471409, Erscheint auch als Druck-Ausgabe 9780120471409, http://app.knovel.com/hotlink/toc/id:kpMSDTSW04/multiresolution-signal-decomposition X:KNOVEL Verlag Volltext, https://zbmath.org/?q=an:0947.94001 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext, http://app.knovel.com/hotlink/toc/id:kpMSDTSW04/multiresolution-signal-decomposition Zum Online-Dokument DE-Zi4, DE-Zi4 2019-01-31T16:03:28Z
spellingShingle Haddad, Paul R., Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets, This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decompos., 4.6 LeGall-Tabatabai PR Filter Bank4.7 Princen-Bradley QMF; 4.8 Optimal PR-QMF Design for Subband Image Coding; 4.9 Performance of PR-QMF Families; 4.10 Aliasing Energy in Multiresolution Decomposition; 4.11 Time and Frequency Localizations; 4.12 GTC and NER Performance; 4.13 Summary; Chapter 5. Wavelet Transform; 5.1 Time-Frequency Decompositions; 5.2 The Short-Time Fourier Transform; 5.3 The Wavelet Transform; 5.4 Multiresolution Signal Decomposition; 5.5 Wavelet Regularity and Wavelet Families; 5.6 Biorthogonal Wavelets and Filter Banks; 5.7 Discussions and Conclusion; 5.8 Epilogue, Appendix A: Resolution of the Identity and InversionAppendix B: Orthonormality in Frequency; Appendix C: Problems; Index, Chapter 3. Theory of Subband Decomposition3.1 Multirate Signal Processing; 3.2 Bandpass and Modulated Signals; 3.3 Mth Band, Mirror, and Power Complementary Filters; 3.4 Two-Channel Filter Banks; 3.5 M-Band Filter Banks; 3.6 Cascaded Lattice Structures; 3.7 IIR Subband Filter Banks; 3.8 Two-Dimensional Subband Decomposition; 3.9 Quantization Effects in Filter Banks; 3.10 Summary; Chapter 4. Filterbank Families: Design and Performance; 4.1 Binomial QMF-Wavelet Filters; 4.2 Maximally Flat Filters; 4.3 Bernstein QMF-Wavelet Filters; 4.4 Johnston QMF Family; 4.5 Smith-Barnwell PR-CQF Family, Front Cover; Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets; Copyright Page; Table of Contents; Preface; Chapter 1. Introduction; 1.1 Introduction; 1.2 Why Signal Decomposition?; 1.3 Decompositions: Transforms, Subbands, and Wavelets; 1.4 Performance Evaluation; Chapter 2. Orthogonal Transforms; 2.1 Signal Expansions in Orthogonal Functions; 2.2 Transform Efficiency and Coding Performance; 2.3 Fixed Transforms; 2.4 Parametric Modeling of Signal Sources; 2.5 Lapped Orthogonal Transforms; 2.6 2D Transform Implementation; 2.7 Summary, Signal processing Digital techniques, Coding theory, Signal processing ; Digital techniques
swb_id_str 516838644
title Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
title_auth Multiresolution Signal Decomposition Transforms, Subbands, and Wavelets
title_full Multiresolution Signal Decomposition Transforms, Subbands, and Wavelets
title_fullStr Multiresolution Signal Decomposition Transforms, Subbands, and Wavelets
title_full_unstemmed Multiresolution Signal Decomposition Transforms, Subbands, and Wavelets
title_short Multiresolution Signal Decomposition
title_sort multiresolution signal decomposition transforms subbands and wavelets
title_sub Transforms, Subbands, and Wavelets
topic Signal processing Digital techniques, Coding theory, Signal processing ; Digital techniques
topic_facet Signal processing, Coding theory, Signal processing ; Digital techniques, Digital techniques
url http://app.knovel.com/hotlink/toc/id:kpMSDTSW04/multiresolution-signal-decomposition, https://zbmath.org/?q=an:0947.94001