Effective Video Coding algorithm for Substation Video and Environment Surveillance System

다국어 초록 (Multilingual Abstract)

Guangdong Power Grid Corporation has put forward and implemented based on IP network digital, Linux, industrial grade layered architecture of substation video and environment surveillance system. In order to improve video coding efficiency and meet requirements of users on HD images resolution of substation video and environment surveillance system, this paper proposes an improved implicit motion information inter prediction algorithm for P slice in H.264 based on the spatio-temporal adaptive localized learning model. This algorithm essentially takes advantage of the temporal and spatial correlations that may exist within frames at the block level, and reduces the bits required for encoding motion information while retaining or even improving encoding quality. The simulation results show that the proposed algorithm improves encoding efficiency compared with the H.264 standard with 0.10 dB (QCIF) and 0.17 dB (WQVGA) average PSNR gain, with relatively increase in complexity.