Non-local patch-based methods were until recently state-of-the-art for image denoising but
are now outperformed by convolutional neural networks (CNNs). Yet they are still the best …

Non-local patch based methods were until recently state-of-the-art for image denoising but
are now outperformed by CNNs. Yet they are still the state-of-the-art for video denoising, as …

Sparse and low-rank models have been widely studied in the literature of signal processing
and computer vision. However, as the dimensionality of dataset increases (eg, multispectral …

Non-local patch-based methods were until recently the state of the art for image denoising
but are now outperformed by CNNs. In video denoising, however, they are still competitive …

A frame recursive video denoising method computes each output frame as a function of only
the current noisy frame and the previous denoised output. Frame recursive methods were …

The advancement of imaging devices and countless images generated everyday pose an
increasingly high demand on image denoising, which still remains a challenging task in …

Denoising is an essential part of any image-or video-processing pipeline. Unfortunately, due
to time-processing constraints, many pipelines do not consider the use of modern denoisers …

Filtering multi-dimensional images such as color images, color videos, multispectral images
and magnetic resonance images is challenging in terms of both effectiveness and efficiency …

Anomaly detectors address the difficult problem of detecting automatically exceptions in a
background image, that can be as diverse as a fabric or a mammography. Detection …

In this article we propose a new recursive video denoising method with high performance.
The method is recursive and uses only the current frame and the previous denoised one. It …