多尺度空间基于集中度判定的二维稳像算法

摘要

二轴运动平台由于震动、非一致性摩擦等因素造成视频序列出现抖动,同时外部噪声,光照变化等对图像特征提取、匹配等存在严重影响导致运动向量估计错误,本文提出一种在多尺度空间基于集中度判定的二维稳像算法.通过在多尺度空间下提取视频序列的不变特征,采用深度优先最邻近搜索算法,寻找匹配点对,然后计算匹配点对的集中度,通过最优集中化原则,建立不同层次的计算模型估算二维运动空间的补偿参数,实现抖动视频的亚像素精度补偿.实验采用320 × 240pixels灰度图像序列测试,本文算法稳像精度高,运动估计时间仅为随机抽样一致性算法的13%,有效提升了整个稳像算法的性能.%The vibration and friction factors of two-axis motion platform cause video jitter and because of image feature extraction and matching influenced by illumination variation, noise and so on, the wrong motion vector will be estimated.The multi-scale space two dimension high precision video stabilization algorithm is proposed based on concentration degree. Invariant features are extracted, and then the depth first nearest neighbor search algorithm is used to get the matching double points. At last, concentration degree is computed, and different computing models are built to estimate compensation parameters by optimal concentration degree principle. 320 × 240 pixels gray video sequence is used in experiment, and the algorithm proposed in this paper has high precision. The estimation time is just 13％ of Random Sample Consensus (RANSAC), which improves the performance of video stabilization.