Intelligent multi-camera video surveillance is a multidisciplinary field related to computer
vision, pattern recognition, signal processing, communication, embedded computing and …

Blind image denoising is an important yet very challenging problem in computer vision due
to the complicated acquisition process of real images. In this work we propose a new …

Real-world image noise removal is a long-standing yet very challenging task in computer
vision. The success of deep neural network in denoising stimulates the research of noise …

Hazy images captured under ill-posed scenarios with scattering medium (ie haze, fog, or
smoke) are contaminated in visibility. Inevitably, these images are further degraded by …

Most of previous image denoising methods focus on additive white Gaussian noise (AWGN).
However, the real-world noisy image denoising problem with the advancing of the computer …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Modelling and analyzing noise in images is a fundamental task in many computer vision
systems. Traditionally, noise has been modelled per color channel assuming that the color …

Typical video footage captured using an off-the-shelf camcorder suffers from limited dynamic
range. This paper describes our approach to generate high dynamic range (HDR) video …

Above-ground biomass (AGB) provides a vital link between solar energy consumption and
yield, so its correct estimation is crucial to accurately monitor crop growth and predict yield …

Image denoising algorithms often assume an additive white Gaussian noise (AWGN)
process that is independent of the actual RGB values. Such approaches are not fully …