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Discrete Wavelet Transform: A Signal Processing Approach By D. Sundararajan

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Sales Rank: #3350647 in Books
Published on: 2016-03-07
Original language: English
Dimensions: 9.90" h x .90" w x 6.90" l, 1.49 pounds
Binding: Hardcover
344 pages

Review
"Doubtless, this nice book will stimulate the practical education in the theory of DWT and its applications." (Zentralblatt MATH 2016) Doubtless, this nice book will stimulate the practical education in the theory of DWT and its applications.

Review

This well-written textbook is an introduction to the theory of discrete wavelet transform (DWT) and its applications in digital signal and image processing. The DWT is presented by the author from a digital signal processing point of view. This book is mainly written for broad readership of graduate students and researchers in physics, computer science, and engineering with special interest in digital signal and image processing. The author demonstrates clearly the properties of the DWT by numerous examples and figures. All computations can be realized by MATLAB programs available at the website of this book.

The contents of this textbook is divided into three parts. The first part (with Chapters 2 – 7) has preliminary character and presents the essentials of digital signal processing (such as operations of discrete signals, convolution and correlation, Fourier analysis of discrete signals, z-transforms of discrete signals, finite impulse response (FIR) filters, and multirate digital signal processing).

The core of the book is the second part (with Chapters 8 – 14) which presents the theory of the DWT and some extended wavelet transforms. Since most of the concepts of the DWT are easy to understand by studying the Haar DWT, the author describes the Haar DWT first. Then some orthogonal DWT’s (such as Daubechies filters of length 4 and Coiflet filters of length 6) are designed. The often used biorthogonal DWT’s are presented too. Some implementation aspects of the DWT using typical filters are discussed. As extensions of DWT the author describes the discrete wavelet packet transform, discrete stationary wavelet transform, and dual-tree DWT. The dual-tree DWT provides good directional selectivity and is nearly shift-invariant.

In the last part (with Chapters 15 – 16), two of the major applications of the DWT are presented. The image compression of digital images (with short description of the image compression standard JPEG 2000) and signal denoising are examined.

Each chapter ends with a short summary and many exercises. Answers of selected exercises are given too. Doubtless, this nice book will stimulate the practical education in the theory of DWT and its applications.

Reviewer: Manfred Tasche (Rostock)

From the Back Cover

This easily accessible text makes the learning of the discrete wavelet transform (DWT) easy to understand. Relatively new, DWT is fast becoming a widely used technique in signal and image processing applications, and is essential to know for all signal processing specialists. To facilitate learning for students and professionals with general engineering backgrounds, the author presents DWT using a unique signal processing approach instead of the usual mathematical approaches. The book also includes a large number of examples and figures that illustrate various concepts.

Presents DWT from a digital signal processing point of view, in contrast to the usual mathematical approach, making it highly accessible
Offers a comprehensive coverage of related topics, including convolution and correlation, Fourier transform, FIR filter, orthogonal and biorthogonal filters
Organized systematically, starting from the fundamentals of signal processing to the more advanced topics of DWT and Discrete Wavelet Packet Transform
Written in a clear and concise manner with abundant examples, figures and detailed explanations
Features a companion website that has several MATLAB programs for the implementation of the DWT with commonly used filters

Discrete Wavelet Transform: A Signal Processing Approach with its clarity and concision, as well as numerous examples, is written with graduate and advanced signal processing students in mind. Industry researchers and professionals will also find it an accessible and comprehensive refresher guide.

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