10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62101572)
10.13039/501100012166-National Key Research and Development Program of China (Grant Number: 2020YFA0713504)
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摘要：
Images obtained by compressive push-broom hyperspectral imaging systems may be affected by serious stripe noise, which will significantly reduce the image quality and affect the subsequent image processing. In this paper, we propose a destriping method via matrix decomposition and sparsity constraints for compressive hyperspectral images (CoHSIs). The original noise-free CoHSI is decomposed into a spectral information matrix and a spatial information matrix. The sparsity of spatial information matrix, the smoothness of spectral information matrix and the sparsity of stripe noise are used to re...
