In this paper, we provide a novel data set designed for Camera-independent color
constancy research. Camera independence corresponds to the robustness of an algorithm's …

In this paper, we provide a novel dataset designed for camera invariant color constancy
research. Camera invariance corresponds to the robustness of an algorithm's performance …

Most digital camera pipelines use color constancy methods to reduce the influence of
illumination and camera sensor on the colors of scene objects. The highest accuracy of color …

Color constancy is still one of the biggest challenges in camera color processing.
Convolutional neural networks have been able to improve the situation but there are still …

Achieving color constancy is an important part of image preprocessing pipeline of
contemporary digital cameras. Its goal is to eliminate the influence of the illumination color …

Improvements in color constancy have arisen from the use of convolutional neural networks
(CNNs). However, the patch-based CNNs that exist for this problem are faced with the issue …

Color constancy is the ability of the human visual system to perceive constant colors for a
surface despite changes in the spectrum of the illumination. In computer vision, the main …

Color constancy is a well-studied topic in color vision. Methods are generally categorized as
(1) low-level statistical methods,(2) gamut-based methods, and (3) learning-based methods …

Contemporary approaches frame the color constancy problem as learning camera specific
illuminant mappings. While high accuracy can be achieved on camera specific data, these …

The effects of strong color casts in traditional, learning-based and data-driven color
constancy algorithms is analyzed. This is the first study investigating the response of color …