基于全变分模型的多时相遥感影像厚云去除算法  

Thick cloud removal algorithm for multi-temporal remote sensing images based on total variation model

作　　者：王睿[1] 黄微[1] 胡南强 WANG Rui;HUANG Wei;HU Nanqiang(School of Communication and Information Engineering,Shanghai University,Shanghai 200444,China)

机构地区：[1]上海大学通信与信息工程学院,上海200444

出　　处：《计算机应用》2020年第7期2126-2130,共5页journal of Computer Applications

摘　　要：针对多时相遥感影像厚云去除出现的亮度不一致和明显边界的问题,提出了一种结合全变分模型和泊松方程的多时相遥感影像厚云去除算法。首先,通过多时相遥感影像间共同区域的亮度信息计算亮度校正系数,对图像的亮度进行校正,降低亮度差异对去云结果的影响。然后,基于选择多源全变分模型对亮度校正后的多时相遥感影像进行重建,提高融合结果的空间平滑性及其与原始影像的相似性。最后,利用泊松方程对重建图像的局部区域进行优化。实验结果表明,该算法能够有效解决亮度不一致和边界问题。Brightness inconsistency and obvious boundary affect the reconstruction results of multi-temporal remote sensing images.In order to solve the problem,an improved thick cloud removal algorithm for multi-temporal remote sensing image was proposed by combining total variation model and Poisson equation.Firstly,the brightness correction coefficient was calculated by the brightness information of the common area of multi-temporal remote sensing images in order to correct the brightness of the images,so as to reduce the effect of brightness differences on cloud removal results.Then,multitemporal images after brightness correction were reconstructed based on selective multi-source total variation model,and the fusion results’spatial smoothnesses and their similarities with the original images were improved.Finally,the local areas of the reconstruction image were optimized by using Poisson equation.The experimental results show that this method can effectively solve the problems of brightness inconsistency and boundary.

关 键 词：厚云去除 全变分模型 多时相遥感影像 亮度校正 泊松方程 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]