Application Of Wavelet Transform In Image Processing


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Wavelet Analysis with Applications to Image Processing


Wavelet Analysis with Applications to Image Processing

Author: Lakshman Prasad

language: en

Publisher: CRC Press

Release Date: 1997-06-16


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Wavelet analysis is among the newest additions to the arsenals of mathematicians, scientists, and engineers, and offers common solutions to diverse problems. However, students and professionals in some areas of engineering and science, intimidated by the mathematical background necessary to explore this subject, have been unable to use this powerful tool. The first book on the topic for readers with minimal mathematical backgrounds, Wavelet Analysis with Applications to Image Processing provides a thorough introduction to wavelets with applications in image processing. Unlike most other works on this subject, which are often collections of papers or research advances, this book offers students and researchers without an extensive math background a step-by-step introduction to the power of wavelet transforms and applications to image processing. The first four chapters introduce the basic topics of analysis that are vital to understanding the mathematics of wavelet transforms. Subsequent chapters build on the information presented earlier to cover the major themes of wavelet analysis and its applications to image processing. This is an ideal introduction to the subject for students, and a valuable reference guide for professionals working in image processing.

Signal Analysis and Prediction


Signal Analysis and Prediction

Author: Ales Prochazka

language: en

Publisher: Springer Science & Business Media

Release Date: 1998-12-23


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Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.

Wavelets and Signal Processing


Wavelets and Signal Processing

Author: Hans-Georg Stark

language: en

Publisher: Springer Science & Business Media

Release Date: 2005-10-11


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As the applications of wavelet transform have spread to diverse areas of signal analysis and compression, students and practitioners need a practical introduction and overview. This textbook provides that concise and practical introduction to the underlying foundations and important applications. Through numerous examples and case studies from industry, it demonstrates both the potential and the limits of wavelet techniques, expanding the usual treatment beyond the discrete wavelet transform to the continuous transform. Providing the basics of Fourier transforms and digital filters in the appendix, the text is supplemented with end-of-chapter exercises, MATLAB code, and a short introduction to the MATLAB wavelet toolbox. Students of electrical engineering and engineers in industry can benefit from the concentration on real applications.