Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform
Pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform
复制标题
全色锐化算法通过掩模躲避和非采样平移不变剪切波变换去除薄云
DOI：
10.1117/1.jrs.8.083658
复制
发表时间：
2014
影响因子：
1.7
通讯作者：
Hao, Hong-Xia
中科院分区：
文献类型：
--
作者：
Shi, Cheng;Liu, Fang;Li, Ling-Ling;Hao, Hong-Xia
摘要全色锐化的目的是获得具有更高空间分辨率和更好光谱信息的图像。然而，薄云严重影响了全色锐化图像的分辨率。对于单幅图像，滤波算法被广泛用于去除云。这几种方法都能有效地去除云，但去云后图像细节丢失也比较严重。针对这一问题，提出了一种基于掩模匀光和非采样平移不变剪切波变换（NSST）的全色锐化薄云去除算法。针对低分辨率多光谱图像和高分辨率全色图像中的薄云，采用掩模匀光法进行云的去除。对于去云的LR MS图像，提出了一种自适应主成分分析变换，以平衡全色锐化图像的光谱信息和空间分辨率。针对去云过程中细节丢失的问题，设计了一个权值矩阵，在全色锐化过程中增强云区域的细节，而非云区域保持不变。并通过NSST获得图像的细节信息。在可见光和评价指标上的实验结果表明，该方法能够保持较好的光谱信息和空间分辨率，特别是对于薄云图像。
Abstract The goal of pan-sharpening is to get an image with higher spatial resolution and better spectral information. However, the resolution of the pan-sharpened image is seriously affected by the thin clouds. For a single image, filtering algorithms are widely used to remove clouds. These kinds of methods can remove clouds effectively, but the detail lost in the cloud removal image is also serious. To solve this problem, a pan-sharpening algorithm to remove thin cloud via mask dodging and nonsampled shift-invariant shearlet transform (NSST) is proposed. For the low-resolution multispectral (LR MS) and high-resolution panchromatic images with thin clouds, a mask dodging method is used to remove clouds. For the cloud removal LR MS image, an adaptive principal component analysis transform is proposed to balance the spectral information and spatial resolution in the pan-sharpened image. Since the clouds removal process causes the detail loss problem, a weight matrix is designed to enhance the details of the cloud regions in the pan-sharpening process, but noncloud regions remain unchanged. And the details of the image are obtained by NSST. Experimental results over visible and evaluation metrics demonstrate that the proposed method can keep better spectral information and spatial resolution, especially for the images with thin clouds.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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作者：
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影响因子：
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通讯作者：
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DOI：
10.1109/tgrs.2004.825593
发表时间：
2004-06-01
影响因子：
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DOI：
10.1109/tgrs.2008.916211
发表时间：
2008-05-01
影响因子：
8.2
作者：
Shah, Vijay P.;Younan, Nicolas H.;King, Roger L.
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King, Roger L.