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Linetype Structure Image Denoising Via Improved Finite Ridgelet Transform

Authors: Lian-wei Lu; Peng-lang Shui;

Linetype Structure Image Denoising Via Improved Finite Ridgelet Transform

Abstract

This paper presents an improved finite ridgelet transform (IMFRIT) approach to linetype structure image denoising. The key element of this technique is an improvement of the finite Radon transform, whereby the transform is defined on non-square grid rather than on square one. A linetype structure denoising algorithm, which utilizes IMFRIT, is then developed. In this algorithm, referred to as the slice-based IMFRIT (SIMFRIT) algorithm, the image is first divided into several slices, and then IMFRIT denoising is performed on each slice. Experiment results show that our approach can significantly reduce the "wrap-around" effect which is an annoying problem in FRIT, and well preserve edges at the same time

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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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