Deep Equilibrium Convolutional Sparse Coding for Hyperspectral Image Denoising

Hyperspectral images (HSIs) play a crucial role in remote sensing but are often degraded by complex noise patterns. Ensuring the physical property of the denoised HSIs is vital for robust HSI denoising, giving the rise of deep unfolding-based methods. However, these methods map the optimization of a...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 63; pp. 1 - 14
Main Authors:	Ye, Jin, Wang, Jingran, Xiong, Fengchao, Chen, Jingzhou, Qian, Yuntao
Format:	Journal Article
Language:	English
Published:	New York IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Coding Computational modeling Convolutional codes Convolutional sparse coding (CSC) Correlation deep equilibrium (DEQ) model Encoding Equilibrium Fixed points (mathematics) hyperspectral image (HSI) denoising Hyperspectral imaging Image coding Noise reduction Optimization Physical properties Remote sensing Representations Robustness (mathematics) Similarity Three-dimensional displays Training Transformers
ISSN:	0196-2892, 1558-0644
Online Access:	Get full text
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