Results 21 to 30 of about 37,700 (292)

All of Low-Rank and Sparse: A Recast Total Variation Approach to Hyperspectral Denoising

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Hyperspectral image (HSI) processing tasks frequently rely on spatial–spectral total variation (SSTV) to quantify the local smoothness of image structures.
Haijin Zeng, Shaoguang Huang, Yongyong Chen, Hiep Luong, Wilfried Philips   +4 more
doaj   +1 more source

A nonconvex $$\hbox{TV}_q-l_1$$ TV q - l 1 regularization model and the ADMM based algorithm

Scientific Reports, 2022
The total variation (TV) regularization with $$l_1$$ l 1 fidelity is a popular method to restore the image contaminated by salt and pepper noise, but it often suffers from limited performance in edge-preserving.
Zhuang Fang, Tang Liming, Wu Liang, Liu Hanxin   +3 more
doaj   +1 more source

Tube-Based Taut String Algorithms for Total Variation Regularization

Mathematics, 2020
Removing noise from signals using total variation regularization is a challenging signal processing problem arising in many practical applications.
Artyom Makovetskii, Sergei Voronin, Vitaly Kober, Aleksei Voronin   +3 more
doaj   +1 more source

Multidirectional Anisotropic Total Variation and Its Application in the Tomography of the Surrounding Rock of Coal Mining Faces

Shock and Vibration, 2021
The computed tomography (CT) reconstruction algorithm is one of the crucial components of the CT system. To date, total variation (TV) has been widely used in CT reconstruction algorithms. Although TV utilizes the a priori information of the longitudinal
Bo Chen, Guowei Zhu, Zhenqiang Yang
doaj   +1 more source

Low Dose CT Image Reconstruction Based on Structure Tensor Total Variation Using Accelerated Fast Iterative Shrinkage Thresholding Algorithm

Sensors, 2020
Low dose computed tomography (CT) has drawn much attention in the medical imaging field because of its ability to reduce the radiation dose. Recently, statistical iterative reconstruction (SIR) with total variation (TV) penalty has been developed to low ...
Junfeng Wu, Xiaofeng Wang, Xuanqin Mou, Yang Chen, Shuguang Liu   +4 more
doaj   +1 more source

On the Equivalence of Soft Wavelet Shrinkage, Total Variation Diffusion, Total Variation Regularization, and SIDEs [PDF]

, 2003
Soft wavelet shrinkage, total variation (TV) diffusion, total variation regularization, and a dynamical system called SIDEs are four useful techniques for discontinuity preserving denoising of signals and images. In this paper, we investigate under which
Joachim Weickert, Pavel Mrázek, Variation Regularization, Thomas Brox, Martin Welk, Gabriele Steidl   +5 more
core   +2 more sources

Magnetic resonance imaging enhancement using prior knowledge and a denoising scheme that combines total variation and histogram matching techniques

Frontiers in Applied Mathematics and Statistics, 2023
IntroductionBrain perfusion-weighted images obtained through dynamic contrast studies play a critical and clinical role in diagnosis and treatment decisions. However, due to the patient's limited exposure to radiation, computed magnetic resonance imaging
Vincenzo Schiano Di Cola, Vincenzo Schiano Di Cola, Dea M. L. Mango, Alessandro Bottino, Lorenzo Andolfo, Salvatore Cuomo   +5 more
doaj   +1 more source

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms [PDF]

Physics in Medicine and Biology, 2009
Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can
Jie, Tang, Brian E, Nett, Guang-Hong, Chen   +2 more
openaire   +2 more sources

Color Transfer Using Adaptive Second-Order Total Generalized Variation Regularizer

IEEE Access, 2018
Color transfer is to generate synthetic images by changing the color of target images with new colors obtained from given source images, while the geometrical structure of the synthetic images remains the same. Classical color transfer models use a total
Bin Xie, Chen Xu, Yu Han, Robert K. F. Teng   +3 more
doaj   +1 more source

Improved Generalized IHS Based on Total Variation for Pansharpening

Remote Sensing, 2023
Pansharpening refers to the fusion of a panchromatic (PAN) and a multispectral (MS) image aimed at generating a high-quality outcome over the same area.
Xuefeng Zhang, Xiaobing Dai, Xuemin Zhang, Yuchen Hu, Yingdong Kang, Guang Jin   +5 more
doaj   +1 more source