A Cubic Convolution Interpolation-Based Chroma Subsampling Method for Bayer and RGBW CFA Raw Images

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Abstract

The Bayer and RGBW color filter array (CFA) raw images, denoted by I^Bayer and I^RGB, respectively, have been widely used in consumer markets. In the demosaicking-first compression scheme, chroma subsampling is necessary prior to compressing I^RGB and I^RGBW. Several linear interpolation-based chroma subsampling methods have been developed for I^Bayer, but no nonlinear interpolation-based chroma subsampling methods have targeted the above two CFA image types simultaneously. In this paper, we first propose a nonlinear interpolation-based, namely the cubic convolution interpolation-based (CCI-based), 2× 2 block-distortion function for each 2× 2 CFA block B^CbCr. Next, using the Cauchy-Schwarz inequality, we prove that the proposed block-distortion function is a convex function in the real domain, which further serves as the base of the initial subsampled chroma solution. Then, a CCI-based iterative method is proposed to improve the initial subsampled chroma solution. The results of comprehensive experimental tests using Bayer and RGBW CFA images created from the three RGB full-color datasets, namely IMAX, SCI (screen content images), and CI (classical images), demonstrate that on the Versatile Video Coding (VVC) platform VTM-11.0, the proposed method achieves substantial quality enhancement and quality-bitrate tradeoff merits of the reconstructed Bayer and RGBW CFA images compared with existing chroma subsampling methods.

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Chung, K. L., Leung, T. C., Liu, T. Y., & Tseng, Y. C. (2022). A Cubic Convolution Interpolation-Based Chroma Subsampling Method for Bayer and RGBW CFA Raw Images. IEEE Access, 10, 22687–22699. https://doi.org/10.1109/ACCESS.2022.3154487

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