Hyperspectral unmixing has attracted considerable attentions in recent years and some promising algorithms have been developed. In this paper. collaborative representation–based unmixing (CRU) for hyperspectral images is proposed. Different from imposing the sparseness constraint on training samples in sparse representation. https://www.kingarte.com/product-category/accessories-drain-parts/