Results 11 to 20 of about 39,050 (216)
Overview of Research on Digital Image Denoising Methods [PDF]
SensorsDuring image collection, images are often polluted by noise because of imaging conditions and equipment limitations. Images are also disturbed by external noise during compression and transmission, which adversely affects consequent processing, like ...
Jing Mao +3 more
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Self-Supervised Joint Learning for pCLE Image Denoising [PDF]
SensorsProbe-based confocal laser endoscopy (pCLE) has emerged as a powerful tool for disease diagnosis, yet it faces challenges such as the formation of hexagonal patterns in images due to the inherent characteristics of fiber bundles.
Kun Yang +4 more
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Image denoising method integrating ridgelet transform and improved wavelet threshold. [PDF]
PLoS ONEIn the field of image processing, common noise types include Gaussian noise, salt and pepper noise, speckle noise, uniform noise and pulse noise. Different types of noise require different denoising algorithms and techniques to maintain image quality and
Bingbing Li, Yao Cong, Hongwei Mo
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Multicomponent MR Image Denoising [PDF]
International Journal of Biomedical Imaging, 2009 Magnetic Resonance images are normally corrupted by random noise from the measurement process complicating the automatic feature extraction and analysis of clinical data. It is because of this reason that denoising methods have been traditionally applied to improve MR image quality.
Manjn, José V. +5 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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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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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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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.
Guillermo Sapiro, Guoshen Yu
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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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