A New Saliency-Driven Fusion Method Based on Complex Wavelet Transform for Remote Sensing Images
A New Saliency-Driven Fusion Method Based on Complex Wavelet Transform for Remote Sensing Images
复制标题
一种基于复小波变换的显着性驱动遥感图像融合新方法
DOI：
10.1109/lgrs.2017.2768070
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发表时间：
2017-12
影响因子：
4.8
通讯作者：
Zhang Jue
中科院分区：
文献类型：
--
作者：
Zhang Libao;Zhang Jue
在遥感图像中，对光谱和空间分辨率的要求因区域而异。纹理丰富、边界清晰的区域（如居民区和道路）需要更多的空间细节来更好地描述各种地物，而农田和山脉等区域主要通过光谱特征来区分。然而，现有的遥感图像融合算法大多对整幅图像进行统一处理，忽略了这些重要的需求。针对不同需求的地区采用多样化的融合策略可以有效解决这一问题。本文提出了一种新的基于复小波变换的显著性驱动融合方法。首先，提出了一种基于聚类和谱相异性的自适应显著性检测方法，生成显著性因子，以指示区域对两种分辨率的不同需求。然后，将联合收割机非线性强度-色调-饱和度变换与基于双树复小波变换的多分辨率分析相结合，使两者优势互补。最后，采用显著性因子控制融合过程中的细节注入，以满足不同区域的不同需求。实验结果表明了该方法的有效性和优越性。
In remote sensing images, demands for spectral and spatial resolution vary from region to region. Regions with abundant texture and well-defined boundaries (like residential areas and roads) need more spatial details to provide better descriptions of various ground objects while regions such as farmland and mountains are mainly discriminated by spectral characteristic. However, most existing fusion algorithms for remote sensing images execute a unified processing in the whole image, leaving those important needs out of consideration. The employment of diverse fusion strategy for regions with different needs can provide an effective solution to this problem. In this letter, we propose a new saliency-driven fusion method based on complex wavelet transform. First, an adaptive saliency detection method based on clustering and spectral dissimilarity is presented to generate saliency factor for indicating diverse needs of the two kinds of resolutions in regions. Then, we combine nonlinear intensity–hue–saturation transform with multiresolution analysis based on dual-tree complex wavelet transform in order to complement each other’s advantages. Finally, saliency factor is employed to control the detail injection in the fusion, helping to satisfy different needs of different regions. Experiments reveal the validity and advantages of our proposal.
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通讯作者：
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DOI：
10.1109/tgrs.2013.2286827
发表时间：
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影响因子：
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作者：
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