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Discrete Wavelet Transformations: An Elementary Approach with Applications
 
 
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Discrete Wavelet Transformations: An Elementary Approach with Applications [Hardcover]

Patrick Van Fleet (Author)

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Book Description

047018311X 978-0470183113 January 18, 2008 1
An "applications first" approach to discrete wavelet transformations

Discrete Wavelet Transformations provides readers with a broad elementary introduction to discrete wavelet transformations and their applications. With extensive graphical displays, this self-contained book integrates concepts from calculus and linear algebra into the construction of wavelet transformations and their various applications, including data compression, edge detection in images, and signal and image denoising.

The book begins with a cursory look at wavelet transformation development and illustrates its allure in digital signal and image applications. Next, a chapter on digital image basics, quantitative and qualitative measures, and Huffman coding equips readers with the tools necessary to develop a comprehensive understanding of the applications. Subsequent chapters discuss the Fourier series, convolution, and filtering, as well as the Haar wavelet transform to introduce image compression and image edge detection. The development of Daubechies filtersis presented in addition to coverage of wavelet shrinkage in the area of image and signal denoising. The book concludes with the construction of biorthogonal filters and also describes their incorporation in the JPEG2000 image compression standard.

The author's "applications first" approach promotes a hands-on treatment of wavelet transforma-tion construction, and over 400 exercises are presented in a multi-part format that guide readers through the solution to each problem. Over sixty computer labs and software development projects provide opportunities for readers to write modules and experiment with the ideas discussed throughout the text. The author's software package, DiscreteWavelets, is used to perform various imaging and audio tasks, compute wavelet transformations and inverses, and visualize the output of the computations. Supplementary material is also available via the book's related Web site, which includes an audio and video repository, final project modules, and softwarefor reproducing examples from the book. All software, including the DiscreteWavelets package, is available for use with Mathematica®, MATLAB®, and Maple.

Discrete Wavelet Transformations strongly reinforces the use of mathematics in digital data applications, sharpens programming skills, and provides a foundation for further study of more advanced topics, such as real analysis. This book is ideal for courses on discrete wavelet transforms and their applications at the undergraduate level and also serves as an excellent reference for mathematicians, engineers, and scientists who wish to learn about discrete wavelet transforms at an elementary level.


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Editorial Reviews

Review

"The book is a valuable reference for wavelet applications and the theory of underlying 2-band filterbanks." (Mathematical Reviews, Issue 2009g)

From the Back Cover

An "applications first" approach to discrete wavelet transformations

Discrete Wavelet Transformations provides readers with a broad elementary introduction to discrete wavelet transformations and their applications. With extensive graphical displays, this self-contained book integrates concepts from calculus and linear algebra into the construction of wavelet transformations and their various applications, including data compression, edge detection in images, and signal and image denoising.

The book begins with a cursory look at wavelet transformation development and illustrates its allure in digital signal and image applications. Next, a chapter on digital image basics, quantitative and qualitative measures, and Huffman coding equips readers with the tools necessary to develop a comprehensive understanding of the applications. Subsequent chapters discuss the Fourier series, convolution, and filtering, as well as the Haar wavelet transform to introduce image compression and image edge detection. The development of Daubechies filtersis presented in addition to coverage of wavelet shrinkage in the area of image and signal denoising. The book concludes with the construction of biorthogonal filters and also describes their incorporation in the JPEG2000 image compression standard.

The author's "applications first" approach promotes a hands-on treatment of wavelet transforma-tion construction, and over 400 exercises are presented in a multi-part format that guide readers through the solution to each problem. Over sixty computer labs and software development projects provide opportunities for readers to write modules and experiment with the ideas discussed throughout the text. The author's software package, DiscreteWavelets, is used to perform various imaging and audio tasks, compute wavelet transformations and inverses, and visualize the output of the computations. Supplementary material is also available via the book's related Web site, which includes an audio and video repository, final project modules, and softwarefor reproducing examples from the book. All software, including the DiscreteWavelets package, is available for use with Mathematica®, MATLAB®, and Maple.

Discrete Wavelet Transformations strongly reinforces the use of mathematics in digital data applications, sharpens programming skills, and provides a foundation for further study of more advanced topics, such as real analysis. This book is ideal for courses on discrete wavelet transforms and their applications at the undergraduate level and also serves as an excellent reference for mathematicians, engineers, and scientists who wish to learn about discrete wavelet transforms at an elementary level.


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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
biorthogonal wavelet transformation, soft threshold rule, image compression and edge detection, highpass portion, lowpass portion, modified wavelet transform, computing one iteration, biorthogonal filter pair, stopping indices, wrapping rows, lowpass conditions, pair whose lengths, biorthogonal transform, zero orthogonality conditions, hard threshold rule, dotting row, soft threshold function, quantized transformation, compute one iteration, wavelet transform matrix, bit stream length, wavelet matrices, biorthogonal filters, block matrix multiplication, stopping index
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Computer Lab, Software Development, Proof of Proposition, John Wiley, Use Problem, Van Fleet, Prove Proposition, Proof of Theorem, Repeat Problem, Ingrid Daubechies, Haar Wavelet Transform, Proof of Corollary, Prove Corollary, Characterizing Solutions, Using Proposition, Transform Bit Stream Length, Using Problem, Coiflet Length, Discrete Wavelet Transformations
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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