21 July 2014 Joint demosaicking and zooming using moderate spectral correlation and consistent edge map
Dengwen Zhou, Weiming Dong, Wengang Chen
Author Affiliations +
Abstract
The recently published joint demosaicking and zooming algorithms for single-sensor digital cameras all overfit the popular Kodak test images, which have been found to have higher spectral correlation than typical color images. Their performance perhaps significantly degrades on other datasets, such as the McMaster test images, which have weak spectral correlation. A new joint demosaicking and zooming algorithm is proposed for the Bayer color filter array (CFA) pattern, in which the edge direction information (edge map) extracted from the raw CFA data is consistently used in demosaicking and zooming. It also moderately utilizes the spectral correlation between color planes. The experimental results confirm that the proposed algorithm produces an excellent performance on both the Kodak and McMaster datasets in terms of both subjective and objective measures. Our algorithm also has high computational efficiency. It provides a better tradeoff among adaptability, performance, and computational cost compared to the existing algorithms.
© 2014 SPIE and IS&T 0091-3286/2014/$25.00 © 2014 SPIE and IS&T
Dengwen Zhou, Weiming Dong, and Wengang Chen "Joint demosaicking and zooming using moderate spectral correlation and consistent edge map," Journal of Electronic Imaging 23(4), 043010 (21 July 2014). https://doi.org/10.1117/1.JEI.23.4.043010
Published: 21 July 2014
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Color difference

Statistical analysis

Image processing

Digital cameras

Optical filters

Reconstruction algorithms

MATLAB

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