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 for offering efficient compression without affecting the image quality. The HEVC offers improved performance than the existing compression models. This work develops an approach for video compression by proposing weighted entropy coding and adaptive block search based Rate-Distortion (R-D) trade-off. A new R-D trade-off, named Taylor R-D trade-off, is designed using Taylor series. The adaptive block search algorithm is proposed for initiating the block search process of motion estimation in video coding by selecting the optimal block using the Hexagon Based Tree Search Algorithm (HBTSA), along with the Taylor R-D trade-off. 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 evaluate that the proposed HBTSA method shows improved PSNR and SSIM using Football, coast guard, garden, and, tennis with values 42.717dB, and 0.991, respectively.