Removal of Large-Scale Stripes Via Unidirectional Multiscale Decomposition

Remote Sensing

Xueli Chang¹  Zhiqi Zhang²  Luxiao He³  Xiaoxiao Feng³  Mi Wang³ 

[1] School of Computer, Hubei University of Technology, Wuhan 430068, China;School of Resource and Environment Sciences, Wuhan University, Wuhan 430079, China;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China;

关键词: destriping;    column-by-column nonuniformity correction (ccnuc);    cumulative error;    unidirectional multiscale decomposition;   

DOI  :  10.3390/rs11212472

来源: DOAJ

【 摘 要 】

Stripes are common in remote sensing imaging systems equipped with multichannel time delay integration charge-coupled devices (TDI CCDs) and have different scale characteristics depending on their causes. Large-scale stripes appearing between channels are difficult to process by most current methods. The framework of column-by-column nonuniformity correction (CCNUC) is introduced to eliminate large-scale stripes. However, the worst problem of CCNUC is the unavoidable cumulative error, which will cause an overall color cast. To eliminate large-scale stripes and suppress the cumulative error, we proposed a destriping method via unidirectional multiscale decomposition (DUMD). The striped image was decomposed by constructing a unidirectional pyramid and making difference maps layer by layer. The highest layer of the pyramid was processed by CCNUC to eliminate large-scale stripes, and multiple cumulative error suppression measures were performed to reduce overall color cast. The difference maps of the pyramid were processed by a designed filter to eliminate small-scale stripes. Experiments showed that DUMD had good destriping performance and was robust with respect to different terrains.

【 授权许可】

Unknown