Results 11 to 20 of about 17,318 (265)
Flashlight CNN Image Denoising [PDF]
2020 28th European Signal Processing Conference (EUSIPCO), 2021 This paper proposes a learning-based denoising method called FlashLight CNN (FLCNN) that implements a deep neural network for image denoising. The proposed approach is based on deep residual networks and inception networks and it is able to leverage many more parameters than residual networks alone for denoising grayscale images corrupted by additive ...
Pham Huu Thanh Binh +2 more
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A Triple Deep Image Prior Model for Image Denoising Based on Mixed Priors and Noise Learning
Applied Sciences, 2023 Image denoising poses a significant challenge in computer vision due to the high-level visual task’s dependency on image quality. Several advanced denoising models have been proposed in recent decades. Recently, deep image prior (DIP), using a particular
Yong Hu +4 more
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Image Denoising Using Framelet Transform [PDF]
Engineering and Technology Journal, 2010 In many of the digital image processing applications, observed image ismodeled to be corrupted by different types of noise that result in a noisy version.Hence image denoising is an important problem that aims to find an estimateversion from noisy image ...
Ali K. Nahar, Hadeel N. Abduallah
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Non-local clustering via sparse prior for sports image denoising
EAI Endorsed Transactions on Scalable Information Systems, 2022 This article has been retracted, and the retraction notice can be found here: http://dx.doi.org/10.4108/eai.8-4-2022.173794. Image denoising is very important in image preprocessing. In order to introduce the priori information of external clean image
Ying Zhang
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Image Denoising With Generative Adversarial Networks and its Application to Cell Image Enhancement
IEEE Access, 2020 This paper proposes an image denoising training framework based on Wasserstein Generative Adversarial Networks (WGAN) and applies it to cell image denoising. Cell image denoising is a challenging task which has high requirement on the recovery of feature
Songkui Chen +3 more
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Image denoising algorithm of social network based on multifeature fusion
Journal of Intelligent Systems, 2022 A social network image denoising algorithm based on multifeature fusion is proposed. Based on the multifeature fusion theory, the process of social network image denoising is regarded as the fitting process of neural network, and a simple and efficient ...
Zhao Lanfei, Zhu Qidan
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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
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EURASIP Journal on Image and Video Processing, 2017 Background Digital images are captured using sensors during the data acquisition phase, where they are often contaminated by noise (an undesired random signal).
Monagi H. Alkinani, Mahmoud R. El-Sakka
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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
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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
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