Hyperspectral Image Denoising and Destriping With Adaptive Learnable Subspace Coefficient Tensor Low-Rank Prior

To obtain the clean hyperspectral image (HSI) from the noisy HSI with mixed noise and stripe noise, this article proposes a new and effective adaptive learnable subspace coefficient tensor low-rank (ALSCTLR) model for HSI denoising and destriping based on the unified tensor modeling and subspace rep...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Pengfei Liu, Yihang Du, Liping Sun, Nan Huang, Zhizhong Zheng, Liang Xiao
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	IEEE 2026-01-01
Sarja:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Aiheet:	Data adaptive hyperspectral image (HSI) denoising and destriping learnable subspace representation coefficient (SRC) tensor low-fibered-rank prior tensor nuclear norm (TNN)
Linkit:	https://ieeexplore.ieee.org/document/11498325/
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