AN IMPROVED DESTRIPING METHOD FOR REMOTE SENSING IMAGES

被引:3
|
作者
Dan, Zhiping [1 ,2 ]
Wei, Xing [1 ,2 ]
Sun, Shuifa [1 ,2 ]
Zhou, Gang [3 ]
机构
[1] China Three Gorges Univ, Hubei Key Lab Intelligent Vis Based Monitoring Hy, Yichang 443002, Peoples R China
[2] Collaborat Innovat Ctr Geohazards & Ecoenvironm T, Yichang 443002, Hubei, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China
来源
关键词
Agricultural application; stripe noise; higher-order partial differential; unidirectional total variation; Split-Bregman; REMOVAL; WAVELET; MOMENT; NOISE; MODEL;
D O I
10.2316/Journal.206.2018.1.206-5549
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Aiming at the problem of the stripe noises of agricultural remote sensing (RS) images, an improved destriping method high order unidirectional total variation with split-bregman iteration (HOUTV-SBI) for agricultural RS images is proposed by a higher-order partial differential model. The new method is based on the unidirectional total variation (UTV) model. It could highly performance remove the stripe noises, and effectively suppress the "ripple phenomenon" followed by UTV model. The experiments are compared with other traditional algorithms on the satellite images and their simulation images with two kinds of imaging systems. The results show that our method has good adaptability for removing all kinds of periodic and non-periodic random stripe noises and could provide better practicability.
引用
收藏
页码:104 / 110
页数:7
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