Results 21 to 30 of about 11,782,843 (259)
Locally Adaptive Channel Attention-Based Network for Denoising Images
IEEE Access, 2020 Channel attention has recently been proposed and shown a great improvement in image classification accuracy. In this paper, we show that channel attention can greatly help a low-level vision task, image denoising, as well, and propose channel attention ...
Haeyun Lee, Sunghyun Cho
doaj +1 more source
DCT Image Denoising: a Simple and Effective Image Denoising Algorithm [PDF]
Image Processing On Line, 2011 This work presents a simple but effective denoising algorithm using a local DCT thresholding. This thresholding is applied separately to each color channel after decorrelation. Due to its simplicity and excellent performance, this contribution can be considered as a baseline for comparison and lower bound of performance for newly developed techniques.
Guoshen Yu, Guillermo Sapiro
openaire +2 more sources
A multiresolution framework for local similarity based image denoising [PDF]
, 2012 In this paper, we present a generic framework for denoising of images corrupted with additive white Gaussian noise based on the idea of regional similarity.
Rajpoot, Nasir M. (Nasir Mahmood) +1 more
core +1 more source
Hittite Journal of Science and Engineering, 2023 The main goal of the image denoising is to recover the original image while attaining the structure of the image as much as possible. When the image denoising task is blind, we have no a priori information about the original image.
Kenan Gençol
doaj +1 more source
Edge-aware image denoising algorithm
Journal of Algorithms & Computational Technology, 2018 The key of image denoising algorithms is to preserve the details of the original image while denoising the noise in the image. The existing algorithms use the external information to better preserve the details of the image, but the use of external ...
Xiangning Zhang, Yan Yang, Lening Lin
doaj +1 more source
Semi-Supervised Learning-Based Image Denoising for Big Data
IEEE Access, 2020 In this paper, the research of image noise reduction based on semi-supervised learning is carried out, and the neural network is used to reduce the noise of the image, so as to achieve more stable and good image display ability.
Kun Zhang, Kai Chen
doaj +1 more source
Boosting of Image Denoising Algorithms [PDF]
SIAM Journal on Imaging Sciences, 2015 In this paper we propose a generic recursive algorithm for improving image denoising methods. Given the initial denoised image, we suggest repeating the following “SOS” procedure: (i) Strengthen the signal by adding the previous denoised image to the degraded input image, (ii) Operate the denoising method on the strengthened image, and (iii) Subtract ...
Yaniv Romano, Michael Elad
openaire +4 more sources
Parallel Implementation of Wavelet-based Image Denoising on Programmable PC-grade Graphics Hardware [PDF]
, 2010 The Discrete Wavelet Transform (DWT) has been extensively used for image compression and denoising in the areas of image processing and computer vision. However, the intensive computation of DWT due to its multilevel data decomposition and reconstruction
Xu, Zhijie, Su, Yang
core +1 more source
Plug-and-Play Priors for Model Based Reconstruction [PDF]
, 2013 Model-based reconstruction is a powerful framework for solving a variety of inverse problems in imaging. The method works by combining a forward model of the imaging system with a prior model of the image itself, and the reconstruction is then computed ...
Bouman, Charles A. +5 more
core +1 more source
Image Denoising Using Hybrid Transforms [PDF]
Engineering and Technology Journal, 2007 In this paper a new family of transformation for image denoising ispresented, Multiridgelet and Walidlet transforms, which have been proposedas alternatives to Discrete Wavelet and Multiwavelet transforms.Walidlet transform is an intelligent tool for ...
Walid Mahmoud, Raghad Jassim
doaj +1 more source