Zobrazeno 1 - 10
of 363
pro vyhledávání: '"Kervrann, Charles"'
Image denoising is probably the oldest and still one of the most active research topic in image processing. Many methodological concepts have been introduced in the past decades and have improved performances significantly in recent years, especially
Externí odkaz:
http://arxiv.org/abs/2402.15352
We propose a unified view of non-local methods for single-image denoising, for which BM3D is the most popular representative, that operate by gathering noisy patches together according to their similarities in order to process them collaboratively. O
Externí odkaz:
http://arxiv.org/abs/2402.13816
In many information processing systems, it may be desirable to ensure that any change of the input, whether by shifting or scaling, results in a corresponding change in the system response. While deep neural networks are gradually replacing all tradi
Externí odkaz:
http://arxiv.org/abs/2306.05037
Generators of space-time dynamics in bioimaging have become essential to build ground truth datasets for image processing algorithm evaluation such as biomolecule detectors and trackers, as well as to generate training datasets for deep learning algo
Externí odkaz:
http://arxiv.org/abs/2303.06951
In the past decade, deep neural networks have revolutionized image denoising in achieving significant accuracy improvements by learning on datasets composed of noisy/clean image pairs. However, this strategy is extremely dependent on training data qu
Externí odkaz:
http://arxiv.org/abs/2212.00422
We propose an extension of the well-known Space-Time Cube (STC) visualization technique in order to visualize time-varying 3D spatial data, taking advantage of the interaction capabilities of Virtual Reality (VR). The analysis of multidimensional tim
Externí odkaz:
http://arxiv.org/abs/2206.13213
Timelines are common visualizations to represent and manipulate temporal data, from historical events storytelling to animation authoring. However, timeline visualizations rarely consider spatio-temporal 3D data (e.g. mesh or volumetric models) direc
Externí odkaz:
http://arxiv.org/abs/2206.09910
We propose a unified view of unsupervised non-local methods for image denoising that linearily combine noisy image patches. The best methods, established in different modeling and estimation frameworks, are two-step algorithms. Leveraging Stein's unb
Externí odkaz:
http://arxiv.org/abs/2203.00570
This work tackles the issue of noise removal from images, focusing on the well-known DCT image denoising algorithm. The latter, stemming from signal processing, has been well studied over the years. Though very simple, it is still used in crucial par
Externí odkaz:
http://arxiv.org/abs/2107.14803
Investigation of dynamic processes in cell biology very often relies on the observation in two dimensions of 3D biological processes. Consequently, the data are partial and statistical methods and models are required to recover the parameters describ
Externí odkaz:
http://arxiv.org/abs/1910.10432