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2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), 2017
In recent years, there is a significant development in the field of image denoising. It involves the methods from both spatial domain as well as transform domain. In this paper, we are proposing a hybrid based denoising technique applicable for an image corrupted by Gaussian noise. The method uses both spatial and transforms domains.
B N Aravind, K V Suresh
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In recent years, there is a significant development in the field of image denoising. It involves the methods from both spatial domain as well as transform domain. In this paper, we are proposing a hybrid based denoising technique applicable for an image corrupted by Gaussian noise. The method uses both spatial and transforms domains.
B N Aravind, K V Suresh
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Attention-guided CNN for image denoising
Neural Networks, 2020Deep convolutional neural networks (CNNs) have attracted considerable interest in low-level computer vision. Researches are usually devoted to improving the performance via very deep CNNs. However, as the depth increases, influences of the shallow layers
Chunwei Tian +5 more
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SCS 2003. International Symposium on Signals, Circuits and Systems. Proceedings (Cat. No.03EX720), 2004
The SAR images are corrupted by speckle noise. A new denoising method for this kind of images is reported in this paper. Inspired from the classical Donoho's denoising method, the procedure presented in this paper uses a new type of discrete wavelet transform, entitled Diversity Enhanced Discrete Wavelet Transform, DEDWT and a new filtering strategy ...
M. Kovaci, D. Isar, A. Isar
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The SAR images are corrupted by speckle noise. A new denoising method for this kind of images is reported in this paper. Inspired from the classical Donoho's denoising method, the procedure presented in this paper uses a new type of discrete wavelet transform, entitled Diversity Enhanced Discrete Wavelet Transform, DEDWT and a new filtering strategy ...
M. Kovaci, D. Isar, A. Isar
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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, K. J. Ray Liu
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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, K. J. Ray Liu
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2010
We present a novel probabilistic algorithm for image noise removal. The algorithm is inspired by the Google PageRank algorithm for ranking hypertextual world wide web documents and based upon considering the topological structure of the photometric similarity between image pixels. We provide computationally efficient strategies for obtaining a solution
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We present a novel probabilistic algorithm for image noise removal. The algorithm is inspired by the Google PageRank algorithm for ranking hypertextual world wide web documents and based upon considering the topological structure of the photometric similarity between image pixels. We provide computationally efficient strategies for obtaining a solution
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A Complete Review on Image Denoising Techniques for Medical Images
Neural Processing Letters, 2023Amandeep Kaur, Guanfang Dong
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A non-local algorithm for image denoising
Computer Vision and Pattern Recognition, 2005A. Buades, B. Coll, J. Morel
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A comprehensive review of image denoising in deep learning
Multimedia tools and applications, 2023Rusul Sabah Jebur +3 more
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