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WDFB Contourlet and Shearing Invariant for Image Denoising

Authors: Peng Zhang; Lin Ni;

WDFB Contourlet and Shearing Invariant for Image Denoising

Abstract

We have proposed a new implementation of contourlet, namely, WDFB contourlet which is very efficient for image denoising. We also find two reliable methods for norm estimation, i.e. Monte-Carlo estimation and polyphase impulse reconstruction. The former is fast, simple yet reliable, while the latter can exactly reconstruct the contourlet basis, thus lead to precise results. Then shearing invariant (SI) is proposed as a novel tool for further denoising improvement, especially for multiscale directional transforms. Finally, numerical experiments are presented to support our conclusions.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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