Results 71 to 80 of about 5,751 (196)

Directional Global Three-part Image Decomposition

, 2015
We consider the task of image decomposition and we introduce a new model coined directional global three-part decomposition (DG3PD) for solving it. As key ingredients of the DG3PD model, we introduce a discrete multi-directional total variation norm and ...
Gottschlich, Carsten, Thai, Duy Hoang
core   +1 more source

An Unsupervised Image Enhancement Method Based on Adaptation Region Divisions

IET Image Processing, Volume 19, Issue 1, January/December 2025.
This paper proposes an image enhancement method that combines traditional techniques with deep learning. It converts images to Lab color space, calculates texture complexity, adaptation region divisions and uses a convolutional autoencoder for noise reduction.
Kaijun Zhou, Weiyi Yuan, Yemei Qin
wiley   +1 more source

Rollover Mechanism Methodology of LNG Tank with Gas-Liquid Stratification Based on Curvelet Finite Element Method and Large Eddy Simulation Technology

Journal of Applied Fluid Mechanics, 2018
The rollover phenomenon of LNG tank has great threat to secure storage of LNG, therefore the Curvelet finite element method combing the large eddy simulation technology to analyze the rollover mechanism.
B. Zhao, S. Han, L. Xu, C. Shi, D. Gao, Y. D. Zhang   +5 more
doaj  

Multiresolution Analysis Using Wavelet, Ridgelet, and Curvelet Transforms for Medical Image Segmentation

International Journal of Biomedical Imaging, 2011
The experimental study presented in this paper is aimed at the development of an automatic image segmentation system for classifying region of interest (ROI) in medical images which are obtained from different medical scanners such as PET, CT, or MRI ...
Shadi AlZubi, Naveed Islam, Maysam Abbod
doaj   +1 more source

2D Empirical Transforms. Wavelets, Ridgelets, and Curvelets Revisited

SIAM Journal on Imaging Sciences, 2014
A recently developed new approach, called ``Empirical Wavelet Transform'', aims to build 1D adaptive wavelet frames accordingly to the analyzed signal. In this paper, we present several extensions of this approach to 2D signals (images). We revisit some well-known transforms (tensor wavelets, Littlewood-Paley wavelets, ridgelets and curvelets) and show
Gilles, Jérôme, Tran, Giang, Osher, Stanley   +2 more
openaire   +2 more sources

Deconvolution based on the curvelet transform [PDF]

Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2004
This paper describes a new deconvolution algorithm, based on both the wavelet transform and the curvelet transform. It extends previous results which were obtained for the denoising problem. Using these two different transformations in the same algorithm allows us to optimally detect in the same time isotropic features, well represented by the wavelet ...
Nguyen, Mai K., Starck, Jean-Luc, Murtagh, F.   +2 more
openaire   +2 more sources

Histopathology Image Enhancement Using Multi‐Resolution Deep Learning Techniques

IET Image Processing, Volume 19, Issue 1, January/December 2025.
Accurate analysis of histopathology images is critical for reliable disease diagnosis and effective treatment planning. However, the resolution limitations of digital pathology scanners can hinder the visibility of fine cellular details, potentially impacting diagnostic accuracy and patient outcomes. In this study, we present a comprehensive comparison
Meriem Touhami, Zaka Ur Rehman, Md Jahid Hasan, Mohammad Faizal Ahmad Fauzi, Sarina Binti Mansor   +4 more
wiley   +1 more source

Recognition method of low-resolution coal-rock images based on curvelet transform

矿业科学学报, 2017
Considering the limitations of wavelet in image representation-that it is only optimal in representing point singularities and difficult to extract curve features of coal and rock images, a new recognition method for low-resolution coal-rock images based
Wu Yunxia, Zhang Hong
doaj  

Local energy‐based multimodal medical image fusion in curvelet domain

IET Computer Vision, 2016
Various multimodal medical images like computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography, single photon emission CT and structural MRI have different characteristics and carry different types of complementary ...
Richa Srivastava, Om Prakash, Ashish Khare   +2 more
doaj   +1 more source

Extreme Value Analysis of Empirical Frame Coefficients and Implications for Denoising by Soft-Thresholding

, 2013
Denoising by frame thresholding is one of the most basic and efficient methods for recovering a discrete signal or image from data that are corrupted by additive Gaussian white noise.
Antoniadis, Antoniadis, Axel Munk, Berkner, Borup, Breiman, Brown, Cai, Cai, Candès, Candès, Candès, Candès, Chesneau, Chesneau, Christensen, Cohen, Cohen, Coifman, Daubechies, Daubechies, de Haan, Dette, Do, Do, Donoho, Donoho, Donoho, Donoho, Embrechts, Gao, Guo, Guo, Guo, Hall, Hall, Hall, Hall, Härdle, Johnstone, Kerkyacharian, Labate, Lang, Leadbetter, Li, Mallat, Markus Haltmeier, Munk, Nason, Ng, Pesquet, Slepian, Starck, Šidák   +53 more
core   +1 more source