Machine learning, particularly deep learning (DL), has become a central and state-of-the-art
method for several computer vision applications and remote sensing (RS) image …

Abstract Unmanned Aerial Vehicle (UAV) has seen a dramatic rise in popularity for remote-
sensing image acquisition and analysis in recent years. It has brought promising results in …

Due to the scattering and absorption of light, the captured image under sand-dust weather
has serious color shift and poor visibility, which can affect the application of computer vision …

Color constancy is one of the key steps in the process of image formation in digital cameras.
Its goal is to process the image so that there is no influence of illumination color on the …

In the image processing pipelines of digital cameras, one of the first steps is to achieve
invariance in terms of scene illumination, namely computational color constancy. Usually …

For the imaging signal processing (ISP) pipeline of digital image devices, it is of high
significance to remove undesirable illuminant effects and obtain color invariance, commonly …

Deep learning methods have achieved a large step forward in many computer vision
applications. With mechanisms such as attention, deep models can now guide themselves …

Computational color constancy (CCC) is a fundamental prerequisite for many computer
vision tasks. The key of CCC is to estimate illuminant color so that the image of a scene …

Abstract Land Remote Sensing data analysis presents a distinctive Artificial Intelligence (AI)
research paradigm bolstered through its rich collection of data, which are high-dimensional …

In this article we show the change in paradigm occurred in color constancy algorithms: from
a pre-processing step in image understanding, to the exploitation of image understanding …