基于特征匹配的电子稳像优化技术

针对特征匹配的电子稳像算法存在特征点提取耗时多、准确度不高以及特征点误匹配等问题,从特征点提取及特征点匹配两个方面采取了优化措施,采用基于快速分割特征点提取算法更快地提取特征点,并把特征点定位准确度提高到亚像素级；引入随机采样一致性算法消除误匹配的特征点对,减少场景中局部运动的影响,提高了全局运动参量的估计准确性.实验结果表明,经优化技术处理后,视频稳像准确度高、速度快,能够在存在平移、缩放、旋转及局部有相对运动等情况时保持良好的视频稳像效果.

Optimization Technique of Electronic Image Stabilization Based on Feature Matching

Electronic image stabilization still exists some problems, such as high time-consuming，low accuracy, high eror matching probability and so on. The paper takes appropriate measures to solove these problems from two aspects: feature points extraction and matching. Firstly, the FAST algorithm is adpoted to extracte the feature points, and positional precision of the feature points is improved to the level of sub-pixel. Then the RANSAC algorithm is used to eliminate the error matched points, avoid the interference of relative movement, and the global motion parameters calculated is more accurate. Experimental results show that a more higher precision and faster speed is obtained, which can also be applied for the complex shaking video containing translation, rotation shake and relative movement.