A survey of orthogonal moments for image representation: Theory, implementation, and evaluation
Image representation is an important topic in computer vision and pattern recognition. It
plays a fundamental role in a range of applications toward understanding visual contents …
plays a fundamental role in a range of applications toward understanding visual contents …
A total variation with joint norms for infrared and visible image fusion
R Nie, C Ma, J Cao, H Ding… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A single infrared image or visible image for the same scene is usually insufficient to
simultaneously reveal the infrared objects and the scene details. Thus, image fusion …
simultaneously reveal the infrared objects and the scene details. Thus, image fusion …
A denoising algorithm for partial discharge measurement based on the combination of wavelet threshold and total variation theory
J Tang, S Zhou, C Pan - IEEE Transactions on Instrumentation …, 2019 - ieeexplore.ieee.org
In electrical engineering, partial discharge (PD) measurement is frequently employed to
detect insulation defects and judge insulation conditions of high-voltage electrical …
detect insulation defects and judge insulation conditions of high-voltage electrical …
Single image denoising via multi-scale weighted group sparse coding
Nonlocal self-similarity (NSS) property of natural images, which means that the structure of
the image sub-patches will appear repeatedly within a certain area, has been widely …
the image sub-patches will appear repeatedly within a certain area, has been widely …
Low-rank with sparsity constraints for image denoising
Recent works on providing proper sparse or low-rank priors have shown to result in good
quality image restoration performance. The nonlocal self-similarity (NSS) of images …
quality image restoration performance. The nonlocal self-similarity (NSS) of images …
An efficient reversible data hiding using SVD over a novel weighted iterative anisotropic total variation based denoised medical images
Computed tomography (CT) advancement and extensive usage have raised the public's
worry regarding the patient's associated radiation dose. Reducing the radiation dose may …
worry regarding the patient's associated radiation dose. Reducing the radiation dose may …
3D geometrical total variation regularized low-rank matrix factorization for hyperspectral image denoising
The total variation (TV) regularization has been widely used in hyperspectral image (HSI)
denoising owing to its powerful capabilities in terms of structure preservation. However …
denoising owing to its powerful capabilities in terms of structure preservation. However …
Mixed Noise Removal for Hyperspectral Image With -SSTV Regularization
L Zhang, Y Qian, J Han, P Duan… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Hyperspectral images (HSIs) are usually corrupted by various types of mixed noises, which
degrades the qualities of acquired images and limits the subsequent applications. In this …
degrades the qualities of acquired images and limits the subsequent applications. In this …
Orthogonal polynomial embedded image kernel
Preprocessing operations of images and video frame sequences are beneficial in computer
vision algorithms. For example, smoothing frames is used to eliminate noise; while …
vision algorithms. For example, smoothing frames is used to eliminate noise; while …
A hybrid structural sparse model for image restoration
W Yuan, H Liu, L Liang, W Wang, D Liu - Optics & Laser Technology, 2024 - Elsevier
Structural sparse model (SSM) has achieved great success in various image inverse
problems. However, most existing methods just use a single norm, ie, l 1-or l 2-norm, to …
problems. However, most existing methods just use a single norm, ie, l 1-or l 2-norm, to …