Bayesian method application for color demosaicking

Jin Wang; Jiaji Wu; Zhensen Wu; Marco Anisetti; Gwanggil Jeon

doi:10.1117/1.OE.57.5.053102

9 May 2018 Bayesian method application for color demosaicking

Jin Wang, Jiaji Wu, Zhensen Wu, Marco Anisetti, Gwanggil Jeon

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Optical Engineering, Vol. 57, Issue 5, 053102 (May 2018). https://doi.org/10.1117/1.OE.57.5.053102

Abstract

This study presents a Bayesian approach based on a color image demosaicking algorithm. The proposed method is composed of pointwise and patchwise measurements. The estimation of the missing pixel is formulated as a maximum a posteriori and a minimum energy function. By utilizing Bayesian theory and some prior knowledge, the missing color information is estimated with a statistics-based approach. Under the maximum a posteriori and Bayesian framework, the desired target image corresponds to the optimal reconstruction given the mosaicked image. Compared with existing demosaicking methods, the proposed algorithm improves the CPSNR, S-CIELAB, FSIM, and zipper effect measurements while maintaining high efficiency. Moreover, it handles Gaussian and Poisson noisy images better than other conventional images.

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Jin Wang, Jiaji Wu, Zhensen Wu, Marco Anisetti, and Gwanggil Jeon "Bayesian method application for color demosaicking," Optical Engineering 57(5), 053102 (9 May 2018). https://doi.org/10.1117/1.OE.57.5.053102

Received: 1 November 2017; Accepted: 4 April 2018; Published: 9 May 2018

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