基于Harris图像拼接的全景视频稳像算法

对于背景变换和抖动分量比较小的视频序列，传统稳像算法不能直接适用，本文提出一种基于Harris图像拼接的全景稳像算法。首先采用Prewitt算子提取出图像的边缘信息，在此基础上进行分区的Harris特征点检测；然后结合NCC（normalized cross correlation）算法与RANSAC（random sample consensus）算法实现图像间的特征点精确匹配，接着利用加权平均融合的方法进行图像融合；最后对融合后的全景图像进行剪裁，完成图像补偿，输出稳定的视频序列。实验结果表明:改进的Harris算法提高了算法效率以及正确特征点数量，并且本文稳像算法实时性较好，能够有效消除视频抖动并输出稳定的视频序列。

Panoramic Video Image Stabilization Algorithm Based on Harris Image Stitching

Traditional image stabilization algorithms cannot be directly applicable for video sequences with small background transformation and jitter components. In this study, a panoramic image stabilization algorithm based on the Harris image mosaic is proposed. First, the Prewitt operator was used to extract the edge information of the image, and then, Harris feature points were detected. Subsequently, both NCC and RANSAC algorithms are combined to achieve the exact matching of feature points between images, and the weighted average fusion method is used for image fusion. Finally, the fused panoramic image is clipped to complete image compensation and output a stable video sequence. The experimental results show that the improved Harris algorithm improves the algorithm efficiency and number of correct feature points. Moreover, the image stabilization algorithm in this study demonstrated good real-time performance, which can effectively eliminate video jitter and output stable video sequences.