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Temporal noise reduction of Bayer matrixed video data

Authors: A. BOSCO; M. MANCUSO; BATTIATO, SEBASTIANO; G. SPAMPINATO;

Temporal noise reduction of Bayer matrixed video data

Abstract

This paper describes a new approach for noise reduction of video sequences that directly processes raw data frames acquired by an image sensor. The proposed noise reduction filter operates on Bayer matrixed video sequences instead of the canonical YUV format allowing saving of resources in terms of time and space; this is particularly relevant for real time processing. Noise level is constantly monitored in order to change the filter strength adaptively. Experiments show the effectiveness of the proposed approach.

Country
Italy
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    popularity
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    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
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!
10
Average
Top 10%
Top 10%
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