Provides easy learning and understanding of DWT from a signal processing point of view
“This well-written textbook is an introduction to the theory of discrete wavelet transform (DWT) and its applications in digital signal and image processing.”
-- Prof. Dr. Manfred Tasche - Institut für Mathematik, Uni Rostock
Full review at https://zbmath.org/?q=an:06492561
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Dr. D. Sundararajan, Department Head of Electrical and Electronics Engineering, Adhiyamaan College of Engineering, India.
Dr. Sundararajan obtained his PhD in Electrical Engineering at Concordia University, Montreal, Canada in 1988. As the principle inventor of the latest family of DFT algorithms, he has written three books, three Patents (which have been granted by US, Canada and Britain), and several papers in IEEE Transactions and in the Proceedings of IEEE Conference.
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.
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.
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.
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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