基于薄云厚度分布评估的遥感影像高保真薄云去除方法

doi:10.11772/j.issn.1001-9081.2018051149

计算机应用 ›› 2018, Vol. 38 ›› Issue (12): 3596-3600.DOI: 10.11772/j.issn.1001-9081.2018051149

• 虚拟现实与多媒体计算 • 上一篇下一篇

基于薄云厚度分布评估的遥感影像高保真薄云去除方法

汪月云, 黄微, 王睿

上海大学通信与信息工程学院, 上海 200444

收稿日期:2018-06-04 修回日期:2018-07-23 出版日期:2018-12-10 发布日期:2018-12-15
通讯作者: 汪月云
作者简介:汪月云(1991-),女,江苏盐城人,硕士研究生,主要研究方向:遥感图像辐射校正与信息恢复;黄微(1980-),女,湖南汉寿人,讲师,博士,主要研究方向:遥感图像辐射校正与信息恢复;王睿(1994-),男,安徽安庆人,硕士研究生,主要研究方向:遥感图像辐射校正与信息恢复。

High fidelity haze removal method for remote sensing images based on estimation of haze thickness map

WANG Yueyun, HUANG Wei, WANG Rui

School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China

Received:2018-06-04 Revised:2018-07-23 Online:2018-12-10 Published:2018-12-15
Contact: 汪月云

摘要/Abstract

摘要： 针对遥感影像薄云去除易出现地物失真的问题，在传统加性云污染模型的基础上提出了一种改进的薄云去除方法，即基于薄云厚度分布（HTM）评估的高保真薄云去除方法。首先，基于传统的加性薄云去除算法得到HTM，用整个HTM减去HTM中无云区域的平均值，使得HTM满足无云区域的薄云厚度接近于零；然后，对降质影像中的蓝色地物独立估计薄云厚度；最后，用降质影像减去最终优化的不同波段的薄云厚度得到无云影像。对多幅分辨率不同的光学遥感影像进行实验，实验结果表明，所提算法有效解决了蓝色地物失真严重的问题，改进了降质影像的薄云去除效果，提升了在无云区域的数据保真能力。

关键词: 加性云污染模型, 薄云厚度分布, 高保真, 薄云去除, 遥感影像

Abstract: The haze removal of remote sensing image may easily result in ground object distortion. In order to solve the problem, an improved haze removal algorithm was proposed on the basis of the traditional additive haze pollution model, which was called high fidelity haze removal method based on estimation for Haze Thickness Map (HTM). Firstly, the HTM was obtained by using the traditional additive haze removal algorithm, and the mean value of the cloudless areas was subtracted from the whole HTM to ensure the haze thickness of the cloudless areas closed to zero. Then, the haze thickness of blue ground objects was estimated alone in degraded images. Finally, the cloudless image was obtained by subtracting the finally optimized haze thickness map of different bands from the degraded image. The experiments were carried out for multiple optical remote sensing images with different resolution. The experimental results show that, the proposed method can effectively solve the serious distortion problem of blue ground objects, improve the haze removal effect of degrade images, and promote the data fidelity ability of cloudless areas.

Key words: additive haze pollution model, Haze Thickness Map (HTM), high fidelity, haze removal, remote sensing image

中图分类号:

TP751

汪月云, 黄微, 王睿. 基于薄云厚度分布评估的遥感影像高保真薄云去除方法[J]. 计算机应用, 2018, 38(12): 3596-3600.

WANG Yueyun, HUANG Wei, WANG Rui. High fidelity haze removal method for remote sensing images based on estimation of haze thickness map[J]. Journal of Computer Applications, 2018, 38(12): 3596-3600.

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基于薄云厚度分布评估的遥感影像高保真薄云去除方法

High fidelity haze removal method for remote sensing images based on estimation of haze thickness map

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