Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising.

Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising. Research Abstract Details 

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Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising. Abstract Text:

Jinjun Xu,Stanley Osher,

In this paper, we generalize the iterative regularization method and the inverse scale space method, recently developed for total-variation (TV) based image restoration, to wavelet-based image restoration. This continues our earlier joint work with others where we applied these techniques to variational-based image restoration, obtaining significant improvement over the Rudin-Osher-Fatemi TV-based restoration. Here, we apply these techniques to soft shrinkage and obtain the somewhat surprising result that a) the iterative procedure applied to soft shrinkage gives firm shrinkage and converges to hard shrinkage and b) that these procedures enhance the noise-removal capability both theoretically, in the sense of generalized Bregman distance, and for some examples, experimentally, in terms of the signal-to-noise ratio, leaving less signal in the residual.

Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising. Publishing Authors By Initials

J Xu,S Osher,

For similar information science: computing methodologies: signal processing, computer-assisted research abstracts see: information science: computing methodologies: signal processing, computer-assisted research

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Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: IEEE transactions on image processing : a publicat

VOLUME: 16

Page Numbers: 534-44

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ISSN: 1057-7149

DAY: 3

MONTH: Feb

YEAR: 2007

Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising. Information

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LANGUAGE: eng

NlmUniqueID: 9886191

Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising. Keywords Mesh Terms:

KEYWORDS: Signal Processing, Computer-Assisted

MESH TERMS: methods

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Grant and Affiliation Information for Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising.

AFFILIATION: Department of Mathematics, University of California, Los Angeles 90095-1555, USA. jjxu@math.ucla.edu

Country: United States

AGENCY: United States NCRR

GRANT: U54RR021813

ACRONYM: RR

MEDLINETA: IEEE Trans Image Process

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