A Neural System for Deformed Image Motion Estimation and Compensation

• Main Authors: Hsiao, Shih-Chieh, 蕭士傑
• Other Authors: Lin Chin-Teng
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/40625542174151186249

碩士 === 國立交通大學 === 控制工程系 === 84 === In this thesis, a neural system for deformed image motion estimation and compensation with variable-size blocks is proposed, which can be applied to an image sequence compression system. The motion estimation and compensation techniques have been successfully applied in the area of image sequence coding. Many researches on improving the performance of these techniques have been published; many directions are proposed, which can all lead to a better performance than the conventional technique. Among them, the generalized block-matching and variable-size block matching are successfully applied in reducing the data rate of compensation error and motion information, respectively. These two algorithms have their merits, but suffer from their drawbacks. Moreover, reducing the data rate in compensation error is sometimes increasing the data rate in motion information, or vice versa. Based on these two algorithms, we propose and examine several algorithms which are effective in reducing the data rate. We then incorporate these algorithms into a neural system, in which they work together to overcome the disadvantages of individual and keep their merits at the same time. The proposed system can optimally balance the amount of data rate in two aspects (i.e., compensation error and motion information). As experiment result shows, the proposed system outweighs the conventional techniques.