基于对比度Harris的快速鲁棒图像配准算法

为进一步提高配准算法的鲁棒性、速度及自适应程度，提出了一种基于对比度Harris的快速鲁棒图像配准算法.依据中心像素与其邻域像素灰度值差异计算分块图像对比度，自适应地确定其角点检测的阈值，并通过灰度相似性剔除伪角点；在构建的尺度空间中检测角点，解决了Harris算法需凭经验手动设定阈值，所提取的角点分布不均匀，对尺度敏感且含有伪角点的问题；采用斜率和距离约束剔除粗匹配后的部分误配准点对，再通过随机抽样一致性（random sample consensus，RANSAC）进行精配准.实验结果表明，与4种同类配准算法相比，所提出的配准算法对于JPEG压缩、模糊、视角、光照及尺度变化图像都具有更好的鲁棒性，配准正确率更高，自适应性更强，且配准时间大幅减少. 

A Fast and Robust Image Registration Algorithm Based on Contrast Harris

In order to further improve the robustness, speed and adaptability of the image registration algorithm, a fast and robust image registration algorithm based on contrast Harris was proposed. Firstly, the contrast of the block image was calculated according to the difference of the gray value between the central pixel and its neighborhood pixels, and the threshold of the corner detection was determined adaptively. The pseudo corner points were removed by the gray similarity. Then the corner points were detected in the constructed scale space. As a result, the problems were solved, such as scale sensitive of corner points extracted with Harris algorithm, manual setting of threshold, existence of pseudo corner points, uneven distribution. Finally, the partial mismatched pairs of matched points were removed by slope and distance constraint and the matched pairs were finely aligned by random sample consensus. The experimental results show that, compared with four registration algorithms, the proposed registration algorithm possesses better robustness to JPEG compression, blurred images, visual angle, illumination, rotation and scale changes. The accuracy of registration is higher, the degree of adaptation is stronger and the time of registration can be reduced significantly.