"Sparse image and signal processing" - Information and Links:

Sparse image and signal processing - Info and Reading Options

wavelets, curvelets, morphological diversity

Book's cover
The cover of “Sparse image and signal processing” - Open Library.

"Sparse image and signal processing" was published by Cambridge University Press in 2010 - Cambridge, it has 316 pages and the language of the book is English.


“Sparse image and signal processing” Metadata:

  • Title: ➤  Sparse image and signal processing
  • Author:
  • Language: English
  • Number of Pages: 316
  • Publisher: Cambridge University Press
  • Publish Date:
  • Publish Location: Cambridge

“Sparse image and signal processing” Subjects and Themes:

Edition Specifications:

  • Pagination: ➤  xvii, 316 p., [16] p. of plates :

Edition Identifiers:

AI-generated Review of “Sparse image and signal processing”:


"Sparse image and signal processing" Table Of Contents:

  • 1- Introduction to the world of sparsity
  • 2- The wavelet transform
  • 3- Redundant wavelet transform
  • 4- Nonlinear multiscale transforms
  • 5- The ridgelet and curvelet transforms
  • 6- Sparsity and noise removal
  • 7- Linear inverse problems
  • 8- Morphological diversity
  • 9- Sparse blind source separation
  • 10- Multiscale geometric analysis on the sphere
  • 11- Compressed sensing.

"Sparse image and signal processing" Description:

The Open Library:

"Presenting the state of the art in sparse and multiscale image and signal processing, this book weds theory and practice to examine their applications in a diverse range of fields"--Provided by publisher. "This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways. Matlab and IDL code accompany these methods and applications to reproduce the experiments and illustrate the reasoning and methodology of the research available for download at the associated Web site"--Provided by publisher.

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