Results 101 to 110 of about 726,843 (203)

Asymptotic Analysis of Shearlet Transfom for Inpainting

Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2018
Supply of missing data, also known as inpainting, is an important application of image processing.Wavelets are commonly used for inpainting algorithms. Shearlet transform which is an affinetransformation is the improvement of the wavelet transform.
Süleyman Çetinkaya, Cüneyt Yazıcı, Hülya Kodal Sevindir   +2 more
doaj   +1 more source

Deep learning‐based methods for detecting defects in cast iron parts and surfaces

IET Image Processing, Volume 18, Issue 1, Page 47-58, 10 January 2024.
First, this article used multiple data augmentation methods to alleviate the problem of small sample size in casting datasets. Second, attention mechanism was introduced. Finally, a novel feature fusion layer structure was adopted to improve the original network model.
Pengyu Wang, Peng Jing
wiley   +1 more source

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

AIP 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, Xin Xia, Xianqi Liao, Qi Zheng, Changfu Fang, Nanxing Wu   +5 more
doaj   +1 more source

3D Discrete Shearlet Transform and Video Denoising

, 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  

mBCCf: Multilevel Breast Cancer Classification Framework Using Radiomic Features

International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.
Breast cancer characterization remains a significant and challenging issue in contemporary medicine. Accurately distinguishing between malignant and benign breast lesions is crucial for effective diagnosis and treatment. The anatomical structure of malignant breast ultrasound images is more chaotic than that of benign images due to disease pathologies.
Lipismita Panigrahi, Tej Bahadur Chandra, Atul Kumar Srivastava, Neeraj Varshney, Kamred Udham Singh, Shambhu Mahato, Vasudevan Rajamohan   +6 more
wiley   +1 more source

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

Applied 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, Ke Xu, Peng Zhou, Huajie Liu   +3 more
doaj   +1 more source

Sparse representation and image classification with the shearlet transform [PDF]

, 2017
Classical 2D-wavelet transforms have suboptimal compression performance due to its inability to generate sparse representation of discontinuities along lines. This thesis contains investigations of the shearlet transform which in contrast to classical 2D-
Andersson, Robin
core  

Multicomponent microseismic data denoising by 3D shearlet transform

, 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

Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems

Mathematical 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

Edge analysis and identification using the continuous shearlet transform [PDF]

, 2009
It is well known that the continuous wavelet transform has the ability to identify the set of singularities of a function or distribution f. It was recently shown that certain multidimensional generalizations of the wavelet transform are useful to ...
Labate, Demetrio, Lim, Wang-Q, Guo, Kanghui   +2 more
core   +1 more source