信息熵-低通滤波联合掩模云层干扰去除方法  

Cloud interference removal using information entropy-low-pass-filtering combined mask

作　　者：李静 李颖[1] LI Jing;LI Ying(Beijing Institute of Tracking and Telecommunications Technology,Beijing 100094,China)

机构地区：[1]北京跟踪与通信技术研究所,北京100094

出　　处：《中国光学（中英文）》2024年第5期1199-1208,共10页Chinese Optics

摘　　要：为了降低海洋光学遥感图像中云区对海面表面纹理分析的影响,本文开展了信息熵-低通滤波融合掩模的云层干扰去除研究。首先,分析了现有遥感图像去云算法的基本原理及其局限性。在此基础上,提出一种基于信息熵-低通滤波联合掩模的云层干扰去除方法。其中包括对遥感图像的改进矩匹配的去条带预处理、局部信息熵滤波,以及联合低频滤波作为遥感图像中各像元的校正参数。该算法具有复杂度低、处理速度快的特点。实验结果表明:与现有算法相比,本文提出的算法可在低计算复杂度的前提下,大幅增强各区域的纹理细节信息,其平均信息熵可达到7.8以上,对比度可达到60以上,平均梯度可达到200以上;图像细节方面,本文算法能够在不引入伪边缘、非均匀性的前提下,充分展现受云区影响的海表纹理细节,进一步满足高保真度的遥感应用需求。To mitigate the impact of clouds on sea surface texture analysis in marine remote sensing images,this paper studies the removal of cloud interference using an information entropy-low-pass-filter combined mask.Initially,we analyze the fundamental principles and limitations of the existing remote sensing image declouding algorithms,highlighting their unsuitability for applications requiring high fidelity.Subsequently,we propose a cloud interference removal technology based on information entropy-low-pass filtering combined mask.This technology encompasses destriping procedures with improved moment matching for remote sensing images,local information entropy filtering,and joint low-frequency filtering as correction parameters for each pixel in the images.The algorithm is characterized by low complexity and high time efficiency.Experimental results demonstrate that,compared to existing algorithms,the proposed method significantly enhances texture detail information in thin cloud areas and cloud edges while maintaining low computational complexity.It achieves an image information entropy over 7.8,a contrast ratio exceeding 60,and a mean gradient above 200.In comparisons of image details,the proposed algorithm enhances texture details without introducing artifacts or non-uniformities,thereby meeting the high-fidelity requirements for remote sensing applications.

关 键 词：云层检测 干扰去除 信息熵滤波 低通滤波 

分 类 号：TP394.1[自动化与计算机技术—计算机应用技术] TH691.9[自动化与计算机技术—计算机科学与技术]