Image Reconstruction for Electrical Impedance Tomography Using Enhanced Adaptive Group Sparsity With Total Variation
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2017.2728179
Abstract: A novel image reconstruction algorithm for electrical impedance tomography using enhanced adaptive group sparsity with total variation constraint is proposed in this paper. The new algorithm simultaneously utilizes the prior knowledge of regional structure feature… read more here.
Keywords: enhanced adaptive; variation; adaptive group; total variation ... See more keywords
Mixed Noise Removal for Hyperspectral Images Based on Global Tensor Low-Rankness and Nonlocal SVD-Aided Group Sparsity
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3257851
Abstract: In hyperspectral images (HSIs), mixed noise (e.g., Gaussian noise, impulse noise, stripe noise, and deadlines) contamination is a common phenomenon that greatly reduces the visual quality of the image. In recent years, methods combining global… read more here.
Keywords: group sparsity; noise; tensor; low rankness ... See more keywords
Hyperspectral Image Denoising via Robust Subspace Estimation and Group Sparsity Constraint
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3277832
Abstract: Hyperspectral cameras capture electromagnetic information within hundreds of narrow spectral bands, producing hyperspectral images (HSIs) with the capability to accurately characterize the attribute information of objects. However, mixed noise induced by instrument and atmospheric effects… read more here.
Keywords: group sparsity; subspace; subspace estimation; noise ... See more keywords
Group-Sparsity Learning Approach for Bearing Fault Diagnosis
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DOI: 10.1109/tii.2021.3119002
Abstract: Fault impulse extraction under strong background noise and/or multiple interferences is a challenging task for bearing fault diagnosis. Sparse representation has been widely applied to extract fault impulses and can achieve state-of-the-art performance. However, most… read more here.
Keywords: group sparsity; fault diagnosis; sparsity; fault ... See more keywords
FCFusion: Fractal Componentwise Modeling With Group Sparsity for Medical Image Fusion
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3185050
Abstract: Multimodal image fusion is the process of combing relevant biological information that can be used for automated industrial application. In this article, we present a novel framework combining fractal constraint with group sparsity to achieve… read more here.
Keywords: group sparsity; image fusion; fusion;
Cell Detection by Functional Inverse Diffusion and Non-Negative Group Sparsity—Part II: Proximal Optimization and Performance Evaluation
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2018.2868256
Abstract: In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this second part, we focus on our algorithmic contributions. We… read more here.
Keywords: part; functional inverse; negative group; non negative ... See more keywords