Results 301 to 310 of about 18,244,520 (347)

Image Denoising Games

IEEE Transactions on Circuits and Systems for Video Technology, 2013
Based on the observation that every small window in a natural image has many similar windows in the same image, the nonlocal denoising methods perform denoising by weighted averaging all the pixels in a nonlocal window and have achieved very promising denoising results.
Yan Chen 0007, K. J. Ray Liu
openaire   +1 more source

Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising

Computer Vision and Pattern Recognition, 2021
Deep denoiser, the deep network for denoising, has been the focus of the recent development on image denoising. In the last few years, there is an increasing interest in developing unsupervised deep denoisers which only call unorganized noisy images ...
T. Pang, Huan Zheng, Yuhui Quan, Hui Ji
semanticscholar   +1 more source

NTIRE 2023 Challenge on Image Denoising: Methods and Results

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023
This paper reviews the NTIRE 2023 challenge on image denoising (σ = 50) with a focus on the proposed solutions and results. The aim is to obtain a network design capable to produce high-quality results with the best performance measured by PSNR for image
Yawei Li, Yulun Zhang, R. Timofte, L. Gool, Zhaopeng Tu, Kunpeng Du, Hailing Wang, Hanting Chen, Wei Li, Xiaofei Wang, Jie Hu, Yunhe Wang, Xiangyu Kong, Jinlong Wu, Dafeng Zhang, Jianxing Zhang, Shuai Liu, Furui Bai, Chaoyu Feng, Hao Wang, Yuqian Zhang, Guangqi Shao, Xiaotao Wang, Lei Lei, Rongjian Xu, Zhilu Zhang, Yunjin Chen, Dongwei Ren, W. Zuo, Qi Wu, Mingyan Han, Shen Cheng, Haipeng Li, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Jinting Luo, Wen-Jie Lin, Leiting Yu, Haoqiang Fan, Shuaicheng Liu, Aditya Arora, Syed Waqas Zamir, Javier Vazquez-Corral, K. Derpanis, Michael S. Brown, Hao Li, Zhihao Zhao, Jin-shan Pan, Jiangxin Dong, Jinhui Tang, Bo Yang, Jingxiang Chen, LI, Xi Zhang, Zhao-Na Zhang, Jiahuan Ren, Zhicheng Ji, Kang Miao, Suiyi Zhao, Huan Zheng, Yanyan Wei, Kangliang Liu, Xiangcheng Du, Sijie Liu, Yi Zheng, Xingjiao Wu, Cheng Jin, Rajeev Irny, Sriharsha Koundinya, V. Kamath, Gaurav Khandelwal, S. A. Khowaja, Jiseok Yoon, I. Lee, Shijie Chen, Chengqiang Zhao, Huabin Yang, Zhongjian Zhang, Jun-Jia Huang, Yanru Zhang   +80 more
semanticscholar   +1 more source

Improved Denoising Auto-Encoders for Image Denoising

2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2018
Image denoising is an important pre-processing step in image analysis. Various denoising algorithms, such as BM3D, PCD and K-SVD, obtain remarkable effects. Recently a deep denoising auto-encoder has been proposed and shown excellent performance compared to conventional image denoising algorithms.
Qian Xiang, Xuliang Pang
openaire   +1 more source

Multiscale Image Blind Denoising

IEEE Transactions on Image Processing, 2015
Arguably several thousands papers are dedicated to image denoising. Most papers assume a fixed noise model, mainly white Gaussian or Poissonian. This assumption is only valid for raw images. Yet, in most images handled by the public and even by scientists, the noise model is imperfectly known or unknown.
Lebrun, Marc, Colom, Miguel, Morel, Jean-Michel   +2 more
openaire   +3 more sources

Complexity-regularized image denoising

IEEE Transactions on Image Processing, 2001
Summary: We study a new approach to image denoising based on complexity regularization. This technique presents a flexible alternative to the more conventional \(l^2\), \(l^1\), and Besov regularization methods. Different complexity measures are considered, in particular those induced by state-of-the-art image coders.
Juan Liu, Pierre Moulin
openaire   +2 more sources

Flex-DLD: Deep Low-Rank Decomposition Model With Flexible Priors for Hyperspectral Image Denoising and Restoration

IEEE Transactions on Image Processing
Hyperspectral images (HSIs) are composed of hundreds of contiguous waveband images, offering a wealth of spatial and spectral information. However, the practical use of HSIs is often hindered by the presence of complicated noise caused by various factors
Yurong Chen, Hui Zhang, Yaonan Wang, Yimin Yang, Jonathan Wu   +4 more
semanticscholar   +1 more source

Multiwedgelets in Image Denoising

2013
In this paper the definition of a multiwedgelet is introduced. The multiwedgelet is defined as a vector of wedgelets. In order to use a multiwedgelet in image approximation its visualization and computation methods are also proposed. The application of multiwedgelets in image denoising is presented, as well.
openaire   +2 more sources

Image denoising with complex ridgelets

Pattern Recognition, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chen, Guangyi, Kégl, Balázs
openaire   +2 more sources

U2D2Net: Unsupervised Unified Image Dehazing and Denoising Network for Single Hazy Image Enhancement

IEEE transactions on multimedia
Hazy images captured under ill-posed scenarios with scattering medium (i.e. haze, fog, or smoke) are contaminated in visibility. Inevitably, these images are further degraded by noises owing to real-world imaging.
Bosheng Ding, Ruiheng Zhang, Lixin Xu, Guanyu Liu, Shuo Yang, Yumeng Liu, Qi Zhang   +6 more
semanticscholar   +1 more source