Results 21 to 30 of about 102,882 (279)
A Novel Gray Image Denoising Method Using Convolutional Neural Network
IEEE Access, 2022 In order to make the image denoising more effective in high noise level environment, we propose a gray image denoising method using convolutional neural network (ConvNet). By constructing symmetric and dilated convolutional residual network and combining
Yizhen Meng, Jun Zhang
doaj +1 more source
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
Dilated Deep Residual Network for Image Denoising [PDF]
, 2017 Variations of deep neural networks such as convolutional neural network (CNN) have been successfully applied to image denoising. The goal is to automatically learn a mapping from a noisy image to a clean image given training data consisting of pairs of ...
Hu, Kaoning +2 more
core +3 more sources
Dual-domain image denoising [PDF]
2013 IEEE International Conference on Image Processing, 2013 Image denoising methods have been implemented in both spatial and transform domains. Each domain has its advantages and shortcomings, which can be complemented by each other. State-of-the-art methods like block-matching 3D filtering (BM3D) therefore combine both domains. However, implementation of such methods is not trivial.
Knaus, Claude, Zwicker, Matthias
openaire +1 more source
A Geometric Structure Based Non Local Mean Image Denoising Algorithm
IEEE Access, 2023 With the widespread application of image recognition technology, the commercial application value of image denoising is gradually increasing. To optimize the performance of non local mean image denoising algorithms, the similarity of image blocks in this
Lei Shi
doaj +1 more source
Unpaired Image Denoising [PDF]
2020 IEEE International Conference on Image Processing (ICIP), 2020 Deep learning approaches in image processing predominantly resort to supervised learning. A majority of methods for image denoising are no exception to this rule and hence demand pairs of noisy and corresponding clean images. Only recently has there been the emergence of methods such as Noise2Void, where a deep neural network learns to denoise solely ...
Kattakinda, Priyatham +1 more
openaire +2 more sources
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
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
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