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IEEE Transactions on Image Processing
Article . 2016 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Data sources: zbMATH Open
DBLP
Article . 2020
Data sources: DBLP
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Bayer Demosaicking With Polynomial Interpolation

Bayer demosaicking with polynomial interpolation
Authors: Jiaji Wu; Marco Anisetti; Wei Wu 0002; Ernesto Damiani; Gwanggil Jeon;

Bayer Demosaicking With Polynomial Interpolation

Abstract

Demosaicking is a digital image process to reconstruct full color digital images from incomplete color samples from an image sensor. It is an unavoidable process for many devices incorporating camera sensor (e.g., mobile phones, tablet, and so on). In this paper, we introduce a new demosaicking algorithm based on polynomial interpolation-based demosaicking. Our method makes three contributions: calculation of error predictors, edge classification based on color differences, and a refinement stage using a weighted sum strategy. Our new predictors are generated on the basis of on the polynomial interpolation, and can be used as a sound alternative to other predictors obtained by bilinear or Laplacian interpolation. In this paper, we show how our predictors can be combined according to the proposed edge classifier. After populating three color channels, a refinement stage is applied to enhance the image quality and reduce demosaicking artifacts. Our experimental results show that the proposed method substantially improves over the existing demosaicking methods in terms of objective performance (CPSNR, S-CIELAB ΔE*, and FSIM), and visual performance.

Country
Italy
Related Organizations
Keywords

color interpolation; Demosaicking; edge classifier; polynomial interpolation; software; medicine (all); computer graphics and computer-aided design, Image processing (compression, reconstruction, etc.) in information and communication theory

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    popularity
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    influence
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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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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!
52
Top 10%
Top 10%
Top 1%
Green