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AN IMPROVED DESTRIPING METHOD FOR REMOTE SENSING IMAGES

机译:一种改进的遥感图像的解析方法

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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.
机译:针对农业遥感(RS)图像的条纹噪声的问题,提出了一种改进的DASTIPING方法高阶与农业RS图像用于农业RS图像的分裂迭代(Houtv-SBI)的高阶单向总变化 。 新方法基于单向总变化(UTV)模型。 它可以高性能地消除条纹噪声,有效地抑制了“纹波现象”,然后抑制了UTV模型。 将实验与卫星图像上的其他传统算法进行比较及其具有两种成像系统的模拟图像。 结果表明,我们的方法具有良好的适应性,可用于去除各种周期性和非周期性随机条纹噪声,并可提供更好的实用性。

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