Results 91 to 100 of about 1,095 (204)

The algorithm for extracting surface defects from ZrO2 ceramic bearing balls using shearlet transform image enhancement

open access: yesAIP Advances
To solve the problems of noise coverage defect and low contrast between the defect and the background of ZrO2 ceramic bearing balls, a surface defect extraction algorithm based on shearlet transform image enhancement for ZrO2 ceramic bearing balls is ...
Dahai Liao   +5 more
doaj   +1 more source

Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems

open access: yesMathematical Problems in Engineering, Volume 2024, Issue 1, 2024.
In seismic data processing, data recovery including reconstruction of the missing trace and removal of noise from the recorded data are the key steps in improving the signal‐to‐noise ratio (SNR). The reconstruction of seismic data and removal of noise becomes a sparse optimization problem that can be solved by using sparse regularization.
Diriba Gemechu, Francisco Rossomando
wiley   +1 more source

Multicomponent microseismic data denoising by 3D shearlet transform

open access: yes, 2018
The low-magnitude microseismic signals generated by fracture initiation are generally buried in strong background noise, which complicates their interpretation. Thus, noise suppression is a significant step. We have developed an effective multicomponent,
Mirko van der Baan, Chao Zhang
core   +1 more source

Feature Extraction with Discrete Non-Separable Shearlet Transform and Its Application to Surface Inspection of Continuous Casting Slabs

open access: yesApplied Sciences, 2019
A new feature extraction technique called DNST-GLCM-KSR (discrete non-separable shearlet transform-gray-level co-occurrence matrix-kernel spectral regression) is presented according to the direction and texture information of surface defects of ...
Xiaoming Liu   +3 more
doaj   +1 more source

3D Discrete Shearlet Transform and Video Denoising

open access: yes, 2014
This paper introduces a numerical implementation of the 3D shearlet transform, a directional transform which is derived from the theory of shearlets. The shearlet approach belongs to a class of directional multiscale methods emerged during the last 10 ...
Pooran Singh Negi, Demetrio Labate
core  

Spatio-Temporal Video Analysis and the 3D Shearlet Transform

open access: yes, 2018
The automatic analysis of the content of a video sequence has captured the attention of the computer vision community for a very long time. Indeed, video understanding, which needs to incorporate both semantic and dynamic cues, may be trivial for ...
MALAFRONTE, DAMIANO
core   +1 more source

Processing Medical Images by new several mathematics shearlet transform

open access: yes, 2017
Текст статьи не публикуется в открытом доступе в соответствии с политикой журнала.A new methodology is shown to perform medical image processing by the shearlet transform. The contours of the processed images are obtained and compared with those obtained
Zotin, S.   +5 more
core  

A Novel Adaptive Shrinkage Threshold on Shearlet Transform for Image Denoising

open access: yes, 2014
Shearlet is a new multidimensional and multiscale transform which is optimally efficient in representing image containing edges. In this paper an adaptive shrinkage threshold for image de-noising in shearlet domain is proposed.
HUANG, Xu   +5 more
core   +1 more source

Suppressing seismic random noise based on non-subsampled shearlet transform and improved FFDNet

open access: yesFrontiers in Earth Science
Traditional 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
doaj   +1 more source

Analysis and detection of surface discontinuities using the 3D continuous shearlet transform

open access: yes, 2011
Directional multiscale transforms such as the shearlet transform have emerged in recent years for their ability to capture the geometrical information associated with the singularity sets of bivariate functions and distributions. One of the most striking
Kanghui Guo   +3 more
core   +1 more source

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