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This paper presents a modification to the cNMF for unmixing where the image is first segmented and the cNMF is applied to individual segments for endmember extraction. Extracted spectral endmembers from individual segments are clustered in endmember classes to describe the entire image. The approach is compared with the global cNMF. The segmentation-based cNMF better captures subtle differences between...
This paper presents a visual exploratory analysis of an AVIRIS hyperspectral image to understand the interactions between the spatial and spectral domains in hyperspectral unmixing. We show how the global data cloud may not be convex due to spatial constraints on the distribution of the materials in the scene. Furthermore, we show that by segmenting the data cloud in feature space into piecewise convex...
In this paper, we introduce a new method to detect dust clouds on NOAA-AVHRR satellite images. The approach involves the use of the region growing segmentation algorithm. The region growing starts with a set of seed points obtained from the band math image, which is known to be a good indicator of dust clouds due to physical reasons, and the result will be a binary image that represents the improved...
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