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pro vyhledávání: '"Vaksman, Gregory"'
Image denoising (removal of additive white Gaussian noise from an image) is one of the oldest and most studied problems in image processing. An extensive work over several decades has led to thousands of papers on this subject, and to many well-perfo
Externí odkaz:
http://arxiv.org/abs/2301.03362
Autor:
Vaksman, Gregory, Elad, Michael
Supervised neural networks are known to achieve excellent results in various image restoration tasks. However, such training requires datasets composed of pairs of corrupted images and their corresponding ground truth targets. Unfortunately, such dat
Externí odkaz:
http://arxiv.org/abs/2211.09919
In this work we introduce a novel stochastic algorithm dubbed SNIPS, which draws samples from the posterior distribution of any linear inverse problem, where the observation is assumed to be contaminated by additive white Gaussian noise. Our solution
Externí odkaz:
http://arxiv.org/abs/2105.14951
The non-local self-similarity property of natural images has been exploited extensively for solving various image processing problems. When it comes to video sequences, harnessing this force is even more beneficial due to the temporal redundancy. In
Externí odkaz:
http://arxiv.org/abs/2103.13767
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Montreal, BC, Canada, 2021, pp. 1805-1813
The vast work in Deep Learning (DL) has led to a leap in image denoising research. Most DL solutions for this task have chosen to put their efforts on the denoiser's architecture while maximizing distortion performance. However, distortion driven sol
Externí odkaz:
http://arxiv.org/abs/2103.04192
Image denoising is a well-known and well studied problem, commonly targeting a minimization of the mean squared error (MSE) between the outcome and the original image. Unfortunately, especially for severe noise levels, such Minimum MSE (MMSE) solutio
Externí odkaz:
http://arxiv.org/abs/2101.09552
Image denoising is a well studied problem with an extensive activity that has spread over several decades. Despite the many available denoising algorithms, the quest for simple, powerful and fast denoisers is still an active and vibrant topic of rese
Externí odkaz:
http://arxiv.org/abs/1911.07167
Recent work in image processing suggests that operating on (overlapping) patches in an image may lead to state-of-the-art results. This has been demonstrated for a variety of problems including denoising, inpainting, deblurring, and super-resolution.
Externí odkaz:
http://arxiv.org/abs/1602.08510