Color Adaptation and Cloud Removal between Satellite Images via Optimal Transport

Zheng Zhang, Changmiao Hu, Ping Tang, T. Corpetti
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引用次数: 0

Abstract

Cloud-contaminated pixels exist ubiquitously in satellite images, which limit the usability of satellite images and increase the difficulty of image analysis. To reconstruct these pixels, a basic idea is to transfer cloud-free pixels from corresponding multi-temporal images to the target image, and the performance of this category of methods depends on the quality of information transfer between images. We propose in this work a novel pixel reconstruction method based on optimal transport. Our method first conducts an adaptive col-or transfer between multi-temporal images and then replaces cloud-contaminated pixels by transferred cloud-free pixels. The proposed method fully explores the potential of optimal transport to generate a more adaptive color transfer plan and thus ensure a high quality information transfer between images. Compared with other widely used methods, visual and statistical results on Landsat and MODIS images demonstrate the capacity of our method.
基于最优传输的卫星图像间颜色适应与去云
云污染像素在卫星图像中普遍存在,限制了卫星图像的可用性,增加了图像分析的难度。为了重建这些像素,一个基本思路是将相应多时相图像中的无云像素转移到目标图像中,这类方法的性能取决于图像之间信息传递的质量。本文提出了一种基于最优传输的像素重建方法。我们的方法首先在多时间图像之间进行自适应颜色或转移,然后用转移的无云像素替换被云污染的像素。该方法充分挖掘了最优传输的潜力,生成了更自适应的颜色传输方案,从而保证了图像之间高质量的信息传输。与其他常用方法相比,Landsat和MODIS图像的可视化和统计结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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