Self-Similarity and Spectral Correlation Adaptive Algorithm for Color Demosaicking

Most common cameras use a CCD sensor device measuring a single color per pixel. The other two color values of each pixel must be interpolated from the neighboring pixels in the so-called demosaicking process. State-of-the-art demosaicking algorithms take advantage of interchannel correlation locally...

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Bibliographic Details
Published in:IEEE transactions on image processing 2014-09, Vol.23 (9), p.4031-4040
Main Authors: Duran, Joan, Buades, Antoni
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Channel estimation
Color
Correlation
Image color analysis
Image reconstruction
Interpolation
Pixels
State of the art
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Summary:Most common cameras use a CCD sensor device measuring a single color per pixel. The other two color values of each pixel must be interpolated from the neighboring pixels in the so-called demosaicking process. State-of-the-art demosaicking algorithms take advantage of interchannel correlation locally selecting the best interpolation direction. These methods give impressive results except when local geometry cannot be inferred from neighboring pixels or channel correlation is low. In these cases, they create interpolation artifacts. We introduce a new algorithm involving nonlocal image self-similarity in order to reduce interpolation artifacts when local geometry is ambiguous. The proposed algorithm introduces a clear and intuitive manner of balancing how much channel-correlation must be taken advantage of. Comparison shows that the proposed algorithm gives state-of-the-art methods in several image bases.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2014.2341928