Sparse Representation-Based Multi-Focus Image Fusion Method via Local Energy in Shearlet Domain [PDF]
Sensors, 2023 Multi-focus image fusion plays an important role in the application of computer vision. In the process of image fusion, there may be blurring and information loss, so it is our goal to obtain high-definition and information-rich fusion images.
Liangliang Li +3 more
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X-ray Image Enhancement Based on Nonsubsampled Shearlet Transform and Gradient Domain Guided Filtering [PDF]
Sensors, 2022 In this paper, we propose an image enhancement algorithm combining non-subsampled shearlet transform and gradient-domain guided filtering to address the problems of low resolution, noise amplification, missing details, and weak edge gradient retention in
Tao Zhao, Si-Xiang Zhang
doaj +3 more sources
Continuous Shearlet Tight Frames [PDF]
Journal of Fourier Analysis and Applications, 2010 Based on the shearlet transform we present a general construction of continuous tight frames for $L^2(\mathbb{R}^2)$ from any sufficiently smooth function with anisotropic moments.
Grohs, Philipp
core +7 more sources
Multimodality Medical Image Fusion Using Clustered Dictionary Learning in Non-Subsampled Shearlet Transform [PDF]
Diagnostics, 2023 Imaging data fusion is becoming a bottleneck in clinical applications and translational research in medical imaging. This study aims to incorporate a novel multimodality medical image fusion technique into the shearlet domain.
Manoj Diwakar +7 more
doaj +3 more sources
TDFusion: When Tensor Decomposition Meets Medical Image Fusion in the Nonsubsampled Shearlet Transform Domain. [PDF]
Sensors (Basel), 2023 In this paper, a unified optimization model for medical image fusion based on tensor decomposition and the non-subsampled shearlet transform (NSST) is proposed.
Zhang R, Wang Z, Sun H, Deng L, Zhu H.
europepmc +2 more sources
Brinjal leaf diseases detection based on discrete Shearlet transform and Deep Convolutional Neural Network. [PDF]
PLoS One, 2023 Different diseases are observed in vegetables, fruits, cereals, and commercial crops by farmers and agricultural experts. Nonetheless, this evaluation process is time-consuming, and initial symptoms are primarily visible at microscopic levels, limiting ...
Abisha S +3 more
europepmc +2 more sources
Noise Suppression and Edge Preservation for Low-Dose COVID-19 CT Images Using NLM and Method Noise Thresholding in Shearlet Domain. [PDF]
Diagnostics (Basel), 2022 In the COVID-19 era, it may be possible to detect COVID-19 by detecting lesions in scans, i.e., ground-glass opacity, consolidation, nodules, reticulation, or thickened interlobular septa, and lesion distribution, but it becomes difficult at the early ...
Diwakar M +7 more
europepmc +2 more sources
An Image Fusion Method of SAR and Multispectral Images Based on Non-Subsampled Shearlet Transform and Activity Measure. [PDF]
Sensors (Basel), 2022 Synthetic aperture radar (SAR) is an important remote sensing sensor whose application is becoming more and more extensive. Compared with traditional optical sensors, it is not easy to be disturbed by the external environment and has a strong penetration.
Huang D, Tang Y, Wang Q.
europepmc +2 more sources
Clifford-Valued Shearlet Transforms on Cl(P,Q)-Algebras
Journal of Mathematics, 2022 The shearlet transform is a promising and powerful time-frequency tool for analyzing nonstationary signals. In this article, we introduce a novel integral transform coined as the Clifford-valued shearlet transform on Cl(p,q) algebras which is designed to
Firdous A. Shah +2 more
doaj +2 more sources
Remote Sensing Image Denoising Based on Gaussian Curvature and Shearlet Transform
IEEE Access, 2023 Model-based image denoising methods are well suited for use as image processors in remote sensing systems such as satellites due to their well-developed mathematical theory and low computational cost, but these methods can often only deal with a single ...
Libo Cheng, Pengyu Chen
doaj +2 more sources