Effective Chroma Subsampling and Luma Modification for RGB Full-Color Images Using the Multiple Linear Regression Technique

Abstract

Differing from the traditional chroma subsampling on the YUV image converted from a RGB full-color image, in this paper, we propose a novel and effective chroma subsampling and luma modification (CSLM) method. For each 2 × 2 YUV block, first, a newly reconstructed 2 × 2 RGB full-color blockdistortion model is proposed, and then we propose a multiple linear regression approach to tackle our CSLM method such that the reconstructed 2 × 2 RGB full-color block-distortion can be minimized, achieving significant quality improvement of the reconstructed RGB full-color image. Based on the Kodak and IMAX datasets, the comprehensive experimental results demonstrated that on the versatile video coding (VVC) platform VTM-8.0, our method achieves substantial quality and quality-bitrate tradeoff improvement of the reconstructed RGB full-color images relative to six traditional methods and the three state-of-the-art methods.

Keywords

• Chroma subsampling
• distortion model
• Luma modification
• multiple linear regression
• quality-bitrate tradeoff
• RGB full-color image