Sep 21, 2017 · As sparse representation gradually obtains better and better results in the analysis of hyperspectral imagery and sparsity-based algorithms ...

Abstract: As sparse representation gradually obtains better and better results in the analysis of hyperspectral imagery and sparsity-based algorithms are ...

In addition, a spatially adaptive weighted model is proposed to detect the similarity between central pixel and neighboring pixels, and to make full use of the ...

Abstract—In this paper, a novel spectral–spatial adaptive sparse representation (SSASR) method is proposed for hyperspectral image (HSI) denoising.

To address these problems, this paper proposes an adaptive joint sparse representation and multi-task learning detector with locality information (JSRMTL-ALI).

In this paper, we propose a new sparsity-based algorithm for automatic target detection in hyperspectral imagery (HSI). This algorithm is based on the ...

In this paper, we investigate the structural changes of local image patches in different bands and their correlation with RGB observation.

In this article, improved sparse representation approaches using adaptive spatial support are proposed for effective target detection in HSI. For conventional ...

Abstract: With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military and other fields, one of the fundamental tasks is ...

In this article, improved sparse representation approaches using adaptive spatial support are proposed for effective target detection in HSI. For conventional ...