| Summary: | 碩士 === 國立交通大學 === 電子工程系所 === 97 === Motion estimation (ME) processing is the most computational and memory intensive component in H.264 encoder. However, traditional ME algorithms focus on rate and distortion performance and thus do not take memory bandwidth into consideration. Therefore, the rate and distortion performance are not optimized under bandwidth constraint. In this thesis, we propose bandwidth-rate-distortion (B-R-D) optimized ME algorithm to solve the issue mentioned above. First, we mainly propose a B-R-D optimized modeling method to determine an appropriate search range (SR) for maximizing rate distortion efficiency while can dynamically meet the available bandwidth. Then, we propose two methods, skip mode detection with content-aware scheme and SR boundary prediction method, to enhance the performance of B-R-D optimized modeling method. The skip mode detection with content-aware scheme is presented to save the most memory bandwidth and thus gives other complex MBs more bandwidth for better quality, and the SR boundary prediction method is presented to determine a feasible SR boundary for SR refinement. Compared with reference software [3], when coding in low motion sequence, the simulation result shows the proposed BRD design could improve the bandwidth saving up to 70% with almost the same performance at bit rate and PSNR under average search range size 16, and up to 84% with negligible PSNR degradation with skip design added; while coding in high motion sequence, the simulation result shows our design could save average bit rate up to 13% and at the same time increase average PSNR up to 0.1dB under low bandwidth constraint. In summary, our design could achieve the same and sometimes even better performance under various bandwidth constraints and thus it is suitable for improving ME process.
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