摘要
在一般的红外图像拼接过程中,采用传统随机抽样一致(RANSAC)方法,耗时往往会稍长。为了缩短图像拼接所耗费的时间,提出了基于尺度不变特征转换(SIFT)和改进RANSAC的图像拼接方法。先通过SIFT得到特征点和特征描述,然后用改进的RANSAC对不匹配的特征点进行剔除,通过得到的变换矩阵完成图像的融合。在改进RANSAC中,设置0.95和0.85两个阈值,少量迭代后,选择跳出循环、重新选择或者计算出新的迭代次数,新的迭代次数必定比传统迭代次数小,因而达到减少时间的效果。红外图像拼接后,把实验结果与采用传统RANSAC算法的结果进行多方位比较,可以发现本文方法能够达到减少时间的目的。
In common process of infrared image mosaic, using the traditional random sample consensus（RANSAC） method often takes a long time. In order to shorten the time consuming of image mosaic, a method of infrared image mosaic based on scale- invariant feature transform（SIFT） and improved RANSAC is proposed.Firstly, feature points and descriptors are obtained by SIFT algorithm. Then the wrong corresponding feature points are deleted by improved RANSAC. The image fusion is implemented, using the transformational matrix. In the improved RANSAC, we set thresholds of 0.95 and 0.85. After some iterations, we choose to jump out of the loop, reselect or calculate a new iteration number. The new number must be smaller than the old one, so the time consuming is shortened. Comparing the infrared image mosaic results with those results based on traditional RANSAC, we can find that the time consuming of proposed method is shorter.
出处
《激光与光电子学进展》
CSCD
北大核心
2014年第11期129-134,共6页
Laser & Optoelectronics Progress
基金
国家自然科学基金(61072090
61205017
61375007)
上海市浦江人才计划(12PJ1402200)
关键词
红外图像
图像拼接
尺度不变特征转换
随机抽样一致
infrared image
image mosaic
scale-invariant feature transform
random sample consensus
