摘要
在遥感卫星运动成像过程中,卫星相机的高速运动会导致遥感图像出现运动模糊。针对该问题,基于一次拍摄过程中获得的不同积分时间遥感图像序列,提出了一种新的去模糊算法。利用短积分时间图像中提取出的轮廓边缘信息来引导对相邻长积分时间图像模糊核的估计,通过分段求解的思想简化了单次模糊核求解的复杂度;然后使用卷积运算对分段模糊核进行无损重组,极大地提高了模糊核估计的准确性。实验结果表明,所提算法对模糊遥感图像去模糊后的清晰程度有显著提升。
When remote sensing satellites capture images during movement,the highspeed motion of the satellite camera causes motion blur in the remote sensing images.To solve this problem,this paper proposes a new deblurring algorithm based on the remote sensing image sequence with different integration time obtained in one shooting process.This algorithm used contour edge information extracted from short integration time images to guide the estimation of the blurred kernel of the adjacent long integration time images.Furthermore,the algorithm simplified the complexity of the single blurred kernel estimation through the idea of segmented solution.Additionally,the algorithm used the convolution operation to reconstruct the segmented blurred kernel,which greatly improved the accuracy of the blurred kernel estimation.Experimental results show that the proposed algorithm effectively improves the accuracy of blurred kernel estimation and significantly improves the clarity of blurred remote sensing images after deblurring.
作者
刘晨辉
尹增山
高爽
Liu Chenhui;Yin Zengshan;Gao Shuang(Innovation Academy for Microsatellites,Chinese Academy of Sciences,Shanghai 201203,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2022年第8期486-494,共9页
Laser & Optoelectronics Progress
基金
中国科学院国防科技创新重点部署项目(KGFZD135-20-03)。
关键词
遥感图像
图像处理
运动模糊
模糊核
去模糊
remote sensing image
image processing
motion blur
blurred kernel
deblurring