Deep Content-Dependent 3-D Convolutional Sparse Coding for Hyperspectral Image Denoising

Despite the significant successes in hyperspectral image (HSI) denoising, pure data-driven HSI denoising networks still suffer from limited understanding of inference. Deep unfolding (DU) is a feasible way to improve the interpretability of deep network. However, the specialized spatial-spectral DU...

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Bibliographic Details
Published in:	IEEE journal of selected topics in applied earth observations and remote sensing Vol. 17; pp. 4125 - 4138
Main Authors:	Yin, Haitao, Chen, Hao
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	3-D convolution Adaptability Convolution Convolutional codes convolutional sparse coding deep network deep unfolding Encoding Filters Hyperspectral image denoising Hyperspectral imaging Image coding Noise reduction separable convolution Tensors Three-dimensional displays
ISSN:	1939-1404, 2151-1535
Online Access:	Get full text
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