Deep learning techniques have received much attention in the area of image denoising.
However, there are substantial differences in the various types of deep learning methods …

Abstract Neural Radiance Fields (NeRF) is a technique for high quality novel view synthesis
from a collection of posed input images. Like most view synthesis methods, NeRF uses …

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …

We propose a general framework for denoising high-dimensional measurements which
requires no prior on the signal, no estimate of the noise, and no clean training data. The only …

In this paper, we propose a state-of-the-art video denoising algorithm based on a
convolutional neural network architecture. Until recently, video denoising with neural …

Collaborative filters perform denoising through transform-domain shrinkage of a group of
similar patches extracted from an image. Existing collaborative filters of stationary correlated …

Low-light enhancement (LLE) is a fundamental technique for improving the visual
perception and interpretability of images and videos that suffer from low light degradation. In …

Imaging in low light is extremely challenging due to low photon counts. Using sensitive
CMOS cameras, it is currently possible to take videos at night under moonlight (0.05-0.3 lux …

Over the last decade, the number of digital images captured per day has increased
exponentially, due to the accessibility of imaging devices. The visual quality of photographs …

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 …