Results 41 to 50 of about 6,876,175 (322)
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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CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image [PDF]
Computer Vision and Pattern Recognition, 2022 Recently, significant progress has been made on image denoising with strong supervision from large-scale datasets. However, obtaining well-aligned noisy-clean training image pairs for each specific scenario is complicated and costly in practice ...
Reyhaneh Neshatavar +3 more
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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
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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
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Research on Image Denoising in Edge Detection Based on Wavelet Transform
Applied Sciences, 2023 Photographing images is used as a common detection tool during the process of bridge maintenance. The edges in an image can provide a lot of valuable information, but the detection and extraction of edge details are often affected by the image noise ...
Ning You +3 more
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MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion [PDF]
IEEE Transactions on Medical Imaging, 2022 Patient scans from MRI often suffer from noise, which hampers the diagnostic capability of such images. As a method to mitigate such artifacts, denoising is largely studied both within the medical imaging community and beyond the community as a general ...
Hyungjin Chung +2 more
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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
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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
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Hybrid Convolutional and Attention Network for Hyperspectral Image Denoising [PDF]
IEEE Geoscience and Remote Sensing LettersHyperspectral image (HSI) denoising is critical for the effective analysis and interpretation of hyperspectral data. However, simultaneously modeling global and local features is rarely explored to enhance HSI denoising.
Shuai Hu +4 more
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