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In this paper, a novel sparse coding algorithm based on L2,1-norm and manifold regularization is developed to reconstruct remote sensing images.
Abstract—Sparse coding is an important tool in image re- construction. In this paper, a novel sparse coding algorithm based on L2,1-norm and manifold ...
Sparse Coding based on L2,1-norm and Manifold Regularization for Remote Sensing Images. Video Player is loading. Play Video. Play. Mute. Current Time 0:00.
TL;DR: In this paper , a sparse coding algorithm based on L2,1-norm and manifold regularization is developed to reconstruct remote sensing images, ...
Sparse coding based on L2,1-norm and manifold regularization for remote sensing images. Jianjun Yuan, Shifeng Li. Sparse coding based on L2,1-norm and ...
TL;DR: In this article , a sparse coding algorithm based on L2,1-norm and manifold regularization is developed to reconstruct remote sensing images, ...
These sparse coding methods learn both a dictionary and the sparse codes from the original data together under the constraint to l1-norm. However, the ...
"Sparse Coding Based Feature Representation Method for Remote Sensing Images ... The following l1 and l2 regularization terms are commonly used. ... Ye, "Multi-task ...
Feb 7, 2024 · Abstract—The curse of dimensionality and noise corruption are two tough problems that need to be solved in hyperspectral image (HSI) ...
This paper proposes a novel multi-feature hyperspectral image (HSI) classification framework that utilizes joint sparse representation (JSR) to combine ...