A Motion Estimation Method of Predicting SAD based on Sub-Macro-Block Fixed-Sample-Points SSAD

• Main Authors: Kun-Sheng Chen, 陳坤勝
• Other Authors: Jen-Shiun Chiang
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/68230968504468820014

碩士 === 淡江大學 === 電機工程學系碩士在職專班 === 96 === The motion estimation algorithm of video sequence always influences image compressed quality, computational complexity and computational loading. Therefore, the issue of macro blocks matching has been discussed for a long time. In the past, many search methods explored how to find the minimum SAD of candidate blocks in the search area, the Motion Vector, such as the well-known methods-Full Search, Three-Step Search, Four-Step Search, Diamond Search, and Cross Diamond Search, …, etc. However, the methods of Three-Step Search, Four-Step Search, Diamond Search, and Cross Diamond Search not only reduce blocks matching and calculation compared to the Full Search but also have good PSNR. Although it is important to have a good image quality at a real time video display, we should not ignore to reduce the computation complexity and computational loading. This research work focuses on the topic of the search points and run time reduction. We propose to use a few Fixed-Sample-Points of 9 Sub-Macro- Blocks (SMB) that are separated from Candidate Block to calculate average Sub-sample SAD (SSAD), and then to predict Candidate-Block SAD. The Predictive SAD can be used to combine any native search method algorithms for Motion Vector searching. It can reduce computation complexity and computational loading. Based on the localized relationship of Sub-sampling Fixed-Samples-Points and SMBs between Candidate Block and Current Block, we divide the Candidate Block into 9 SMBs to reduce the sub-sampling distortion risk. According to the PSNR simulation, this research work cannot reduce search points and search time but also get an acceptable image quality.