Results 231 to 240 of about 49,854 (268)
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IEEE Transactions on Information Theory, 2000
Summary: The so-called denoising problem, relative to normal models for noise, is formalized such that ``noise'' is defined as the incompressible part in the data while the compressible part defines the meaningful information-bearing signal. Such a decomposition is effected by minimization of the ideal code length, called for by the minimum description
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Summary: The so-called denoising problem, relative to normal models for noise, is formalized such that ``noise'' is defined as the incompressible part in the data while the compressible part defines the meaningful information-bearing signal. Such a decomposition is effected by minimization of the ideal code length, called for by the minimum description
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IEEE Transactions on Image Processing, 2003
Over the past decade, there has been significant interest in fractal coding for the purpose of image compression. However, applications of fractal-based coding to other aspects of image processing have received little attention. We propose a fractal-based method to enhance and restore a noisy image.
Mohsen Ghazel +2 more
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Over the past decade, there has been significant interest in fractal coding for the purpose of image compression. However, applications of fractal-based coding to other aspects of image processing have received little attention. We propose a fractal-based method to enhance and restore a noisy image.
Mohsen Ghazel +2 more
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Denoising by singularity detection
IEEE Transactions on Signal Processing, 1999Summary: A new algorithm for noise reduction using the wavelet transform is proposed. Similar to Mallat's wavelet transform modulus maxima denoising approach, we estimate the regularity of a signal from the evolution of its wavelet transform coefficients across scales.
Tai-Chiu Hsung +2 more
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Sodium Image Denoising Based on a Convolutional Denoising Autoencoder
2019Sodium Magnetic Resonance Imaging (sodium MRI) is an imaging modality that has gained momentum over the past decade, because of its potential ability to become a biomarker for several diseases, ranging from cancer to neurodegenerative pathologies, along with monitoring of tissues metabolism.
Simon Koppers +4 more
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Multi-stage image denoising with the wavelet transform
Pattern Recognition, 2023Wangmeng Zuo, David Zhang, Bob Zhang
exaly
Leveraging end-to-end denoisers for denoising periodic signals
2021 29th European Signal Processing Conference (EUSIPCO), 2021Jules Rio +3 more
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Image denoising review: From classical to state-of-the-art approaches
Information Fusion, 2020Sunil Agrawal +2 more
exaly
Deep learning on image denoising: An overview
Neural Networks, 2020Lunke Fei, Yong Xu, Wangmeng Zuo
exaly
Fringe denoising algorithms: A review
Optics and Lasers in Engineering, 2020Rishikesh Kulkarni, Pramod Rastogi
exaly