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Introducing contrast and luminance normalisation to improve the quality of subtractive resolution merge technique

机译:引入对比度和亮度归一化以提高减法分辨率合并技术的质量

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摘要

Subtractive resolution merge (SRM) is a contemporary image fusion method that produces highly preserved spatial and spectral resolution. This method is limited to dual sensor platforms with specific band ratios between the high-resolution panchromatic image (HRPI) and the low-resolution multispectral image (LRMI). An additional problem with SRM is that some bands are over- or under-represented due to the normalisation function applied. This article provides two modifications that resolve these limitations. SRM builds a synthetic low-resolution panchromatic image (LRPIsyn) from the weighted sum of the LRM1 bands. This image is modified by using a spatially resampled HRPI instead. The second modification is the use of a contrast and luminance index for the normalising function. These two modifications are tested on QuickBird images (multispectral and panchromatic), as well as fusing SPOT-5 (Satellite Pour l'Observation de la Terre) multispectral image and an aerial photograph. The results show improved quantitative metrics and unsupervised classification compared with the standard SRM technique and other contemporary image fusion methods. Both of these modifications are grouped into a patent pending technique that is called contrast and luminance normalised fusion.
机译:减法分辨率合并(SRM)是当代的图像融合方法,可产生高度保留的空间和光谱分辨率。此方法仅限于在高分辨率全色图像(HRPI)和低分辨率多光谱图像(LRMI)之间具有特定波段比率的双传感器平台。 SRM的另一个问题是,由于应用了归一化功能,某些频段的代表过多或不足。本文提供了两种修改来解决这些限制。 SRM根据LRM1波段的加权总和构建合成的低分辨率全色图像(LRPIsyn)。通过使用空间重新采样的HRPI修改此图像。第二修改是将对比度和亮度指数用于归一化功能。在QuickBird图像(多光谱和全色)上,以及在SPOT-5(卫星观测卫星)多光谱图像和航拍照片上进行了这两种修改的测试。结果表明,与标准SRM技术和其他当代图像融合方法相比,定量指标得到了改进,并且无监督分类。这两种修改都归为一项正在申请专利的技术,称为对比度和亮度标准化融合。

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