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
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Bendlet Transform Based Adaptive Denoising Method for Microsection Images [PDF]
Entropy, 2022 Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise that appears in MRI images is commonly governed by a Rician distribution. The bendlets system is a second-order shearlet transform with bent elements.
Shuli Mei +5 more
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Noise reduction by adaptive-SIN filtering for retinal OCT images [PDF]
Scientific Reports, 2021 Optical coherence tomography (OCT) images is widely used in ophthalmic examination, but their qualities are often affected by noises. Shearlet transform has shown its effectiveness in removing image noises because of its edge-preserving property and ...
Yan Hu +4 more
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A Convolution-Based Shearlet Transform in Free Metaplectic Domains
Journal of Mathematics, 2021 The free metaplectic transformation (FMT) is a multidimensional integral transform that encompasses a broader range of integral transforms, from the classical Fourier to the more recent linear canonical transforms. The aim of this study is to introduce a
Tarun K. Garg +3 more
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Suppressing seismic random noise based on non-subsampled shearlet transform and improved FFDNet
Frontiers in Earth ScienceTraditional denoising methods often lose details or edges, such as Gaussian filtering. Shearlet transform is a multi-scale geometric analysis tool which has the advantages of multi-resolution and multi-directivity.
Hua Fan, Yang Zhang, Wenxu Wang, Tao Li
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Mathematische Nachrichten, 2022 AbstractWe develop a distributional framework for the shearlet transform and the shearlet synthesis operator , where is the Lizorkin test function space and is the space of highly localized test functions on the standard shearlet group . These spaces and their duals are called Lizorkin type spaces of test functions and distributions.
Francesca Bartolucci +2 more
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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.
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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
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A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images. [PDF]
Sci RepMulti-Modal Medical Image Fusion (MMMIF) has become increasingly important in clinical applications, as it enables the integration of complementary information from different imaging modalities to support more accurate diagnosis and treatment planning ...
Sengan S +5 more
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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.
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