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Discrete Fourier Analysis and Wavelets: Applications to Signal and Image Processing
 
 
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Discrete Fourier Analysis and Wavelets: Applications to Signal and Image Processing [Hardcover]

S. Allen Broughton (Author), Kurt M. Bryan (Author)
4.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

0470294663 978-0470294666 November 10, 2008 1
A thorough guide to the classical and contemporary mathematical methods of modern signal and image processing

Discrete Fourier Analysis and Wavelets presents a thorough introduction to the mathematical foundations of signal and image processing. Key concepts and applications are addressed in a thought-provoking manner and are implemented using vector, matrix, and linear algebra methods. With a balanced focus on mathematical theory and computational techniques, this self-contained book equips readers with the essential knowledge needed to transition smoothly from mathematical models to practical digital data applications.

The book first establishes a complete vector space and matrix framework for analyzing signals and images. Classical methods such as the discrete Fourier transform, the discrete cosine transform, and their application to JPEG compression are outlined followed by coverage of the Fourier series and the general theory of inner product spaces and orthogonal bases. The book then addresses convolution, filtering, and windowing techniques for signals and images. Finally, modern approaches are introduced, including wavelets and the theory of filter banks as a means of understanding the multiscale localized analysis underlying the JPEG 2000 compression standard.

Throughout the book, examples using image compression demonstrate how mathematical theory translates into application. Additional applications such as progressive transmission of images, image denoising, spectrographic analysis, and edge detection are discussed. Each chapter provides a series of exercises as well as a MATLAB project that allows readers to apply mathematical concepts to solving real problems. Additional MATLAB routines are available via the book's related Web site.

With its insightful treatment of the underlying mathematics in image compression and signal processing, Discrete Fourier Analysis and Wavelets is an ideal book for mathematics, engineering, and computer science courses at the upper-undergraduate and beginning graduate levels. It is also a valuable resource for mathematicians, engineers, and other practitioners who would like to learn more about the relevance of mathematics in digital data processing.


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Editorial Reviews

Review

“Anyone seeking to understand the process and problems of image and signal analysis would do well to read this work. Summing Up: Highly recommended.” (Choice Reviews, June 2009)

"There seems to be a shortage of books that deliver an appropriate mix of theory and applications to an undergraduate math major. I believe that Discrete Fourier Analysis and Wavelets, Applications to Signal and Image Processing helps fill this void...This book is enjoyable to read and pulls together a variety of important topics in the subject at a level that upper level undergraduate mathematics students can understand." (MAA Reviews 2009)

From the Back Cover

A thorough guide to the classical and contemporary mathematical methods of modern signal and image processing

Discrete Fourier Analysis and Wavelets presents a thorough introduction to the mathematical foundations of signal and image processing. Key concepts and applications are addressed in a thought-provoking manner and are implemented using vector, matrix, and linear algebra methods. With a balanced focus on mathematical theory and computational techniques, this self-contained book equips readers with the essential knowledge needed to transition smoothly from mathematical models to practical digital data applications.

The book first establishes a complete vector space and matrix framework for analyzing signals and images. Classical methods such as the discrete Fourier transform, the discrete cosine transform, and their application to JPEG compression are outlined followed by coverage of the Fourier series and the general theory of inner product spaces and orthogonal bases. The book then addresses convolution, filtering, and windowing techniques for signals and images. Finally, modern approaches are introduced, including wavelets and the theory of filter banks as a means of understanding the multiscale localized analysis underlying the JPEG 2000 compression standard.

Throughout the book, examples using image compression demonstrate how mathematical theory translates into application. Additional applications such as progressive transmission of images, image denoising, spectrographic analysis, and edge detection are discussed. Each chapter provides a series of exercises as well as a MATLAB project that allows readers to apply mathematical concepts to solving real problems. Additional MATLAB routines are available via the book's related Web site.

With its insightful treatment of the underlying mathematics in image compression and signal processing, Discrete Fourier Analysis and Wavelets is an ideal book for mathematics, engineering, and computer science courses at the upper-undergraduate and beginning graduate levels. It is also a valuable resource for mathematicians, engineers, and other practitioners who would like to learn more about the relevance of mathematics in digital data processing.


Product Details

  • Hardcover: 360 pages
  • Publisher: Wiley-Interscience; 1 edition (November 10, 2008)
  • Language: English
  • ISBN-10: 0470294663
  • ISBN-13: 978-0470294666
  • Product Dimensions: 9.3 x 6.1 x 0.9 inches
  • Shipping Weight: 1.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,648,157 in Books (See Top 100 in Books)

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4.0 out of 5 stars Signal Processing textbook, June 28, 2011
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This review is from: Discrete Fourier Analysis and Wavelets: Applications to Signal and Image Processing (Hardcover)
Well-written, a nice balance of terse mathematical derivations and plain English interpretation/application, and also a nice balance of exercises involving theory/proof and computations, including "lab" assignments implemented in Matlab. Cons: Still too many typo's in this edition, only some of which are included in the author's website.
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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
convolution theorem, kth quantization interval, appropriate synthesis filters, complex exponential waveforms, aliasing relations, finite length signals, orthogonal filter bank, basic waveforms, many nonzero components, discrete waveforms, cascade algorithm, downsampling operator, perfect reconstruction filter bank, dilation equation, convolution and filtering, circular convolution, synthesis filter bank, analysis filter bank, analysis filters, orthogonal filters, scaling function, integer translates, orthogonal wavelets
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Use Matlab, John Wiley, Matlab's Wavelet Toolbox, Start Matlab, Compression Example, Wavelet Toolbox
Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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