Results 91 to 100 of about 779,839 (204)
Corner detection based on shearlet transform and multi-directional structure tensor
Image corners have been widely used in various computer vision tasks. Current multi-scale analysis based corner detectors do not make full use of the multi-scale and multi-directional structural information.
Mingzhe Wang +7 more
core +1 more source
ABSTRACT Low‐dose computed tomography (CT) images are prone to noise and artifacts caused by photon starvation and electronic noise. Recently, researchers have explored the use of transformer‐based neural networks combined with generative diffusion models, showing promising results in denoising CT images.
Farzan Niknejad Mazandarani +2 more
wiley +1 more source
Calderón–Zygmund theory on some Lie groups of exponential growth
Abstract Let G=N⋊A$G = N \rtimes A$, where N$N$ is a stratified Lie group and A=R+$A= \mathbb {R}_+$ acts on N$N$ via automorphic dilations. We prove that the group G$G$ has the Calderón–Zygmund property, in the sense of Hebisch and Steger, with respect to a family of flow measures and metrics.
Filippo De Mari +3 more
wiley +1 more source
A multi‐path residual network for image denoising based on edge prior information
To overcome the problem of the smoothness and loss of high‐frequency details at edges in image denoising, a multi‐path residual network using edge prior information is proposed. Firstly, the edge is recovered from the noisy image via the edge extraction module.
Xuefei Bai, Yongsong Wan, Weiming Wang
wiley +1 more source
A Novel Multi-Focus Image Fusion Method Based on Dual-Tree Shearlet Transform
In this paper, a multi-focus image fusion method based on Dual-Tree Compactly Supported Shearlet Transform (DT CSST) and Direction Decision Map (DDM) is proposed.
Chang Duan, Shuai Wang, Qihong Huang
doaj +1 more source
Due to the limitation of the seismic data acquisition environment and instrument, seismic data are often subjected to random noise interference. At the same time, random noise is inevitably introduced in the processing of seismic data.
Wen-Long Hou +5 more
doaj +1 more source
An automated fracture trace detection technique using the complex shearlet transform [PDF]
Representing fractures explicitly using a discrete fracture network (DFN) approach is often necessary to model the complex physics that govern thermo-hydro-mechanical–chemical processes (THMC) in porous media.
R. Prabhakaran +4 more
doaj +1 more source
A self‐supervised scheme for ground roll suppression
Abstract In recent years, self‐supervised procedures have advanced the field of seismic noise attenuation, due to not requiring a massive amount of clean labelled data in the training stage, an unobtainable requirement for seismic data. However, current self‐supervised methods usually suppress simple noise types, such as random and trace‐wise noise ...
Sixiu Liu +5 more
wiley +1 more source
Various regularization terms have been proposed for inverse problems. In this work, we investigate the shearlet-based regularization in the context of sparse-view X-ray computed tomography(XCT) reconstruction of industrial parts.
Xiaoya Chen +3 more
doaj +1 more source
Construction of Meyer Wavelet Using Fully Smooth Sigmiod Function
In order to obtain better smooth effect in signal or image reconstruction, the regularity or continuous differentiability of wavelet must be increased as much as possible.
SHAO Yun-hong, DENG Cai-xia, HE Peng
doaj +1 more source

