摘要
由于传统SIFT特征点描述符的复杂性,增加图像拼接的时间,针对这种情况,提出一种快速的红外图像拼接算法。算法首先对序列红外图像提取关键帧;然后对图像畸变和海杂波进行预处理,并限制相邻两幅图像的特征点提取区域,缩短图像拼接时间;最后采用双向匹配法提高配准精度,用高斯渐入渐出法得到无缝拼接的图像。实验结果证明该算法提高了拼接速度,当特征点不是很多时,改进后的SIFT匹配算法在时间上可以达到比较理想的效果。
Because of the complicacy of SIFF feature point descriptor, it will result in more image stitching time. In view of this, we propose a fast infrared image mosaic algorithm. This algorithm extracts the key frames from a sequence of infrared image first, and then preprocesses the image distortion and the sea clutter. In order to shorten image stitching time, this algorithm limits the feature point extraction area between two adjacent images. Finally, it uses bilateral matching method to improve the registration accuracy, and uses Gaussian linear weighting fusion algorithm to get a seamless image. Experimental results prove that the algorithm improves the stitching speed, and when the feature points are not many, the improved SIFT matching algorithm can reach the ideal real-time effects.
出处
《计算机应用与软件》
CSCD
2015年第9期197-200,共4页
Computer Applications and Software
基金
国家自然科学基金项目(61171126)
上海自然科学基金项目(11ZR1415200)
上海重点支撑项目(12250501500)