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Impulse noise removal: Noise detection versus pixel estimation

Authors: Dung Dang; Wenbin Luo;

Impulse noise removal: Noise detection versus pixel estimation

Abstract

This paper proposes a new finding regarding the different roles and significance of noise detection and pixel estimation utilized in the majority of impulse noise removing algorithms. Extensive experimental results will be presented to show that the importance of each method depends on the noise ratio. In other words, by particularly examining how the adaptive median filter (AMF) algorithm [18] employs the two aforementioned methods in comparison with their modified versions as well as the ideal-filtering algorithm, this paper will point out the role that each method plays. The significance of noise detection can be realized at low noise ratio while pixel estimation gains its efficiency as noise ratio increases.

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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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