M. R. Vimala Devi, S. Kalaivani*
Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2459-2476, 2023, DOI:10.32604/iasc.2023.038183
Abstract Spectral unmixing helps to identify different components present in the spectral mixtures which occur in the uppermost layer of the area owing to the low spatial resolution of hyperspectral images. Most spectral unmixing methods are globally based and do not consider the spectral variability among its endmembers that occur due to illumination, atmospheric, and environmental conditions. Here, endmember bundle extraction plays a major role in overcoming the above-mentioned limitations leading to more accurate abundance fractions. Accordingly, a two-stage approach is proposed to extract endmembers through endmember bundles in hyperspectral images. The divide and conquer method is applied as the first… More >
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