Results 71 to 80 of about 566 (171)

Image Sequence Fusion and Denoising Based on 3D Shearlet Transform

Journal of Applied Mathematics, 2014
We propose a novel algorithm for image sequence fusion and denoising simultaneously in 3D shearlet transform domain. In general, the most existing image fusion methods only consider combining the important information of source images and do not deal ...
Liang Xu, Junping Du, Zhenhong Zhang
doaj   +1 more source

SAR Interferogram Filtering of Shearlet Domain Based on Interferometric Phase Statistics

Applied Sciences, 2017
This paper presents a new filtering approach for Synthetic Aperture Radar (SAR) interferometric phase noise reduction in the shearlet domain, depending on the coherent statistical characteristics.
Yonghong He, Jianjun Zhu, Haiqiang Fu, Qinghua Xie, Bing Xu, Bing Zhang   +5 more
doaj   +1 more source

A multi‐path residual network for image denoising based on edge prior information

IET Image Processing, Volume 18, Issue 14, Page 4514-4530, 11 December 2024.
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 self‐supervised scheme for ground roll suppression

Geophysical Prospecting, Volume 72, Issue 7, Page 2580-2598, September 2024.
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, Claire Birnie, Andrey Bakulin, Ali Dawood, Ilya Silvestrov, Tariq Alkhalifah   +5 more
wiley   +1 more source

Random Noise Reduction in Seismic Data by Using Bidimensional Empirical Mode Decomposition and Shearlet Transform

IEEE Access, 2019
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, Rui-Sheng Jia, Hong-Mei Sun, Xing-Li Zhang, Meng-Di Deng, Yu Tian   +5 more
doaj   +1 more source

An automated fracture trace detection technique using the complex shearlet transform [PDF]

Solid Earth, 2019
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, R. Prabhakaran, P.-O. Bruna, G. Bertotti, D. Smeulders   +4 more
doaj   +1 more source

An infrared and visible image fusion network based on multi‐scale feature cascades and non‐local attention

IET Image Processing, Volume 18, Issue 8, Page 2114-2125, 19 June 2024.
This paper introduces a novel infrared and visible image fusion network to address the limitations of auto‐encoder fusion networks. In the designed network, the encoder employs a multi‐branch cascade structure with convolution kernels of different sizes to extract multi‐scale features, and the fusion layer incorporates a non‐local attention module ...
Jing Xu, Zhenjin Liu, Ming Fang
wiley   +1 more source

A Novel Multi-Focus Image Fusion Method Based on Dual-Tree Shearlet Transform

International Journal of Advanced Robotic Systems, 2015
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

An adaptive neuro‐fuzzy inference system optimized by genetic algorithm for brain tumour detection in magnetic resonance images

IET Image Processing, Volume 18, Issue 5, Page 1358-1372, 17 April 2024.
An adaptive neuro‐fuzzy inference system is presented based on an optimization of genetic algorithm to classify normal and abnormal brain tumours. Abstract An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours.
Marzieh Ghahramani, Nabiollah Shiri
wiley   +1 more source

3D shearlet-based regulariation for inverse problems with an application to industrial X-ray computed tomography

e-Journal of Nondestructive Testing
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, Patricio Guerrero, Wenjuan Sun, Wim Dewulf   +3 more
doaj   +1 more source