Wavelets for image processing, in Handbook of Applied Mathematics (J. Satsuma, S. Oishi, and M. Sugihara, eds.), Asakura Publishing Co., pp.512-515, 2013
This section discusses how wavelets and related techniques
are used in image processing, and particularly focuses on
image approximation, compression, denoising, and feature extraction.
One of the main reasons why wavelets are used for so many image processing
applications is their capability to efficiently capture and compactly represent
singular image features such as edges and corners compared to the Fourier or
Wavelets in image processing has a long history.
Marr's research on visual information processing in late 1970s and
the Laplacian pyramid of Burt and Adelson in early 1980s significantly
influenced the development of the Multiresolution Analysis by Mallat
and the compactly supported wavelet orthonormal basis by Daubechies.
the full paper (slightly revised on 04/06/13): PDF file.
me if you have any comments or questions!
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