Wavelet-Based Block Low-Rank Representations for Hyperspectral Denoising
Bin Zhao, Jóhannes R. Sveinsson, Magnus Orn Ulfarsson, Jocelyn Chanussot · 2021
This paper presents a wavelet-based block low-rank representations (WBBLRR) denoising method for hyperspectral images (HSIs). WBBLRR uses 3-D wavelet transformation to decompose HSI into different blocks, where each block utilizes a low-rank representations model to obtain the denoised block, and then uses inverse 3-D wavelet transformation for all the denoised blocks to obtain the denoised HSI. The proposed method is evaluated by using both simulated and real hyperspectral datasets.