Adaptive color filter array demosaicking based on constant hue and local properties of luminance

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Abstract

Most commercial digital cameras use a single electronic sensor overlaid with a color filter array (CFA) to capture imagery. Since only one primary color is sampled in each pixel, the missing color primaries must be reconstructed by interpolation. In this paper, an adaptive demosaicking scheme for CFA interpolation is proposed. The scheme uses intra-channel correlation, color difference correlation, constant hue, and luminance-color difference correlation is proposed. A rough interpolation is first implemented by bilinear interpolation. Then the color difference correlation and constant hue are successively used to update the missing color primaries. To obtain high quality color images, an adaptive algorithm using luminance-color difference correlation and the information of edge direction is iteratively applied to improve the image quality around the edges. Simulation results demonstrate that the image quality of the proposed algorithm is better than that of the approach using color difference correlation in terms of peak signal-to-noise ratio (PSNR). © Springer-Verlag Berlin Heidelberg 2007.

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APA

Chou, C. H., Liu, K. C., & Lee, W. Y. (2007). Adaptive color filter array demosaicking based on constant hue and local properties of luminance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4872 LNCS, pp. 357–370). Springer Verlag. https://doi.org/10.1007/978-3-540-77129-6_33

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