Color demosaicking via robust adaptive sparse representation

Lili Huang; Liang Xiao; Qinghua Chen; Kai Wang

doi:10.1117/1.JEI.24.5.053012

21 September 2015 Color demosaicking via robust adaptive sparse representation

Lili Huang, Liang Xiao, Qinghua Chen, Kai Wang

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Journal of Electronic Imaging, Vol. 24, Issue 5, 053012 (September 2015). https://doi.org/10.1117/1.JEI.24.5.053012

Abstract

A single sensor camera can capture scenes by means of a color filter array. Each pixel samples only one of the three primary colors. We use a color demosaicking (CDM) technique to produce full color images and propose a robust adaptive sparse representation model for high quality CDM. The data fidelity term is characterized by l₁ norm to suppress the heavy-tailed visual artifacts with an adaptively learned dictionary, while the regularization term is encouraged to seek sparsity by forcing sparse coding close to its nonlocal means to reduce coding errors. Based on the classical quadratic penalty function technique in optimization and an operator splitting method in convex analysis, we further present an effective iterative algorithm to solve the variational problem. The efficiency of the proposed method is demonstrated by experimental results with simulated and real camera data.

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Lili Huang, Liang Xiao, Qinghua Chen, and Kai Wang "Color demosaicking via robust adaptive sparse representation," Journal of Electronic Imaging 24(5), 053012 (21 September 2015). https://doi.org/10.1117/1.JEI.24.5.053012

Published: 21 September 2015

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KEYWORDS

Code division multiplexing

Associative arrays

Chemical species

Visualization

Cameras

Image enhancement

Data modeling

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