Improved Pansharpening with Un-Mixing of Mixed MS Sub-Pixels near Boundaries between Vegetation and Non-Vegetation Objects
Improved Pansharpening with Un-Mixing of Mixed MS Sub-Pixels near Boundaries between Vegetation and Non-Vegetation Objects
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DOI：
10.3390/rs8020083
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发表时间：
2016-01
期刊：
影响因子：
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通讯作者：
Hui Li;L. Jing;Liming Wang;Q. Cheng
中科院分区：
文献类型：
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作者：
Hui Li;L. Jing;Liming Wang;Q. Cheng
全色锐化是一种重要的多光谱图像融合技术，它通过融合同一区域的低空间分辨率多光谱图像和高空间分辨率全色图像，得到高空间分辨率的多光谱图像。虽然在过去的几十年中已经提出了许多成功的图像融合算法，以减少融合图像中的光谱失真，这些很少考虑混合MS子像素（MSP）所造成的光谱失真。通常，MSP的融合版本保持混合，尽管一些MSP对应于纯PAN像素。由于植被和非植被（VNV）对象之间的显着的光谱差异，融合版本的MSP VNV边界附近的VNV边界模糊和显着的光谱失真的融合图像。为了减少光谱失真，提出了一种改进的基于haze和ratio的融合方法，实现了VNV边界附近MSP的光谱解混。在该方法中，首先识别VNV边界附近的MSP。然后，根据对应PAN像素的类别，将所识别的MSP定义为纯植被像素或非植被像素。实验WorldView-2和IKONOS图像的城市地区使用该方法产生的融合图像具有显着更清晰的VNV边界和较小的光谱失真比其他几个目前使用的图像融合方法。
Pansharpening is an important technique that produces high spatial resolution multispectral (MS) images by fusing low spatial resolution MS images and high spatial resolution panchromatic (PAN) images of the same area. Although numerous successful image fusion algorithms have been proposed in the last few decades to reduce the spectral distortions in fused images, few of these take into account the spectral distortions caused by mixed MS sub-pixels (MSPs). Typically, the fused versions of MSPs remain mixed, although some of the MSPs correspond to pure PAN pixels. Due to the significant spectral differences between vegetation and non-vegetation (VNV) objects, the fused versions of MSPs near VNV boundaries cause blurred VNV boundaries and significant spectral distortions in the fused images. In order to reduce the spectral distortions, an improved version of the haze- and ratio-based fusion method is proposed to realize the spectral un-mixing of MSPs near VNV boundaries. In this method, the MSPs near VNV boundaries are identified first. The identified MSPs are then defined as either pure vegetation or non-vegetation pixels according to the categories of the corresponding PAN pixels. Experiments on WorldView-2 and IKONOS images of urban areas using the proposed method yielded fused images with significantly clearer VNV boundaries and smaller spectral distortions than several other currently-used image fusion methods.