Traditional grayscale image colorization methods generally have problems such as
distortion and inaccuracy, such as pseudo color enhancement and false color processing …

In this paper we propose the truncated edge-based color constancy. It is based on, and
extends, the edge-based framework by introducing the use of truncated Gaussian filters. The …

Although a number of elaborate color constancy algorithms have been proposed, methods
such as Grey World and Max-RGB are still widely used because of their low computational …

Colorimetric characterization can reduce the distortion of image color information in the
process of reproduction of the display device, so as to ensure that the same image can be …

Color correction is one of essential stages in image processing, which plays an important
role during image acquisition or pre-processing to produce a better color quality, before …

To automatically eliminate the influence of external illumination on the acquired image,
restore the true color information of the object, and provide true and stable color features for …

Color constancy is of important for many computer vision applications, such as image
classification, color object recognition, object tracking and so on. But unlike the human …

Color constancy refers to the ability to make the color of an object not change with the
change of the light color of the scene. The use of convolutional neural networks improves …

Colour constancy is defined as the ability to estimate the actual colours of objects in an
acquired image disregarding the colour of scene illuminant. Despite large variety of existing …

Illumination estimation has been studied for a long time. The algorithms to solve the problem
can be roughly divided into two categories: statistical-based and learning-based. Statistical …