Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects
Due to the proliferation of biomedical imaging modalities, such as Photoacoustic
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc …
Adaptive consistency prior based deep network for image denoising
C Ren, X He, C Wang, Z Zhao - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Recent studies have shown that deep networks can achieve promising results for image
denoising. However, how to simultaneously incorporate the valuable achievements of …
denoising. However, how to simultaneously incorporate the valuable achievements of …
Spectral–spatial hyperspectral image classification with edge-preserving filtering
The integration of spatial context in the classification of hyperspectral images is known to be
an effective way in improving classification accuracy. In this paper, a novel spectral-spatial …
an effective way in improving classification accuracy. In this paper, a novel spectral-spatial …
Feature extraction of hyperspectral images with image fusion and recursive filtering
Feature extraction is known to be an effective way in both reducing computational
complexity and increasing accuracy of hyperspectral image classification. In this paper, a …
complexity and increasing accuracy of hyperspectral image classification. In this paper, a …
[HTML][HTML] Survey of mura defect detection in liquid crystal displays based on machine vision
W Ming, S Zhang, X Liu, K Liu, J Yuan, Z Xie, P Sun… - Crystals, 2021 - mdpi.com
Liquid crystal display (LCD) is a display device based on liquid crystal electro-optic effect,
and LCDs have gradually appeared and have become an indispensable part of people's …
and LCDs have gradually appeared and have become an indispensable part of people's …
Mixed noise removal by weighted encoding with sparse nonlocal regularization
Mixed noise removal from natural images is a challenging task since the noise distribution
usually does not have a parametric model and has a heavy tail. One typical kind of mixed …
usually does not have a parametric model and has a heavy tail. One typical kind of mixed …
Restoration of images corrupted by mixed Gaussian-impulse noise via l1–l0 minimization
In this paper, we study the restoration of images corrupted by Gaussian plus impulse noise,
and propose a l1–l0 minimization approach where the l1 term is used for impulse denoising …
and propose a l1–l0 minimization approach where the l1 term is used for impulse denoising …
A universal denoising framework with a new impulse detector and nonlocal means
B Xiong, Z Yin - IEEE Transactions on Image Processing, 2011 - ieeexplore.ieee.org
Impulse noise detection is a critical issue when removing impulse noise and
impulse/Gaussian mixed noise. In this paper, we propose a new detection mechanism for …
impulse/Gaussian mixed noise. In this paper, we propose a new detection mechanism for …
A new weighted mean filter with a two-phase detector for removing impulse noise
This paper proposes a new weighted mean filter with a two-phase noise detector for image
denoising. Operations are carried out by the detection followed by filtering strategy. For …
denoising. Operations are carried out by the detection followed by filtering strategy. For …
Impulse noise removal using SVM classification based fuzzy filter from gray scale images
In this paper, support vector machine (SVM) classification based Fuzzy filter (FF) is proposed
for removal of impulse noise from gray scale images. When an image is affected by impulse …
for removal of impulse noise from gray scale images. When an image is affected by impulse …