A Fast Linearized Alternating Minimization Algorithm for Constrained High-Order Total Variation Regularized Compressive Sensing
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2944173
Abstract: In this paper, we propose a new high-order total variation regularized model with box constraint for image compressive sensing reconstruction. Because of the separable structure of this model, we can easily decompose into three subproblems… read more here.
Keywords: variation regularized; total variation; alternating minimization; compressive sensing ... See more keywords
Hyperspectral Anomaly Detection With Total Variation Regularized Low Rank Tensor Decomposition and Collaborative Representation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3170072
Abstract: Nowadays, many anomaly detection (AD) methods still have shortcomings in using the spatial information of hyperspectral images (HSIs), which leads to the inability to separate the background and anomalies well. In this letter, a hyperspectral… read more here.
Keywords: information; total variation; low rank; variation regularized ... See more keywords
Surface Defects Detection Using Non-convex Total Variation Regularized RPCA With Kernelization
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2021.3056738
Abstract: Surface defects have an adverse effect on the quality of industrial products, and vision-based defect detection is widely researched due to its objective and stable performance. However, the task is still challenging due to diversified… read more here.
Keywords: variation regularized; total variation; surface; regularized rpca ... See more keywords