Taylor rate-distortion trade-off and adaptive block search for HEVC encoding

Abstract

The advancement in high-efficiency video coding (HEVC) is adapted for defining the subsequent generation compression model to offer efficient compression without affecting the image quality. The HEVC offers improved performance than the existing compression models. Accordingly, this work develops an approach for video compression by proposing weighted entropy coding and adaptive block search-based rate-distortion (R-D) trade-off, named Taylor R-D trade-off. The adaptive block search R-D trade-off, by integrating the hexagon-based tree search algorithm (HBTSA), along with the Taylor R-D trade-off for initiating the block search process of motion estimation in video coding, which selects the optimal block. Initially, the frames are extorted from the input video. Then, the video frames are divided into macroblocks to perform the adaptive block search. Further, the suitable blocks are selected and given to the encoding process by weighted context-adaptive binary arithmetic coding (CABAC) that employs a weighted entropy function to persist the video quality after the compression. The results analysis shows that the proposed HBTSA method has improved PSNR and SSIM values of 42.717dB, and 0.991, respectively, using football, coast guard, garden, and tennis videos.