To achieve computer vision color constancy (CVCC), it is vital but challenging to estimate
scene illumination from a digital image, which distorts the true color of an object. Estimating …

For more than a decade, both academia and industry have focused attention on the
computer vision and in particular the computational color constancy (CVCC). The CVCC is …

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 …

In the human and computer vision, color constancy is the ability to perceive the true color of
objects in spite of changing illumination conditions. Color constancy is remarkably …

Computational colour constancy refers to the problem of obtaining reliable illuminant colour
so that the image can be rectified to generate a new image under the canonical illumination …

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 …

Color constancy is one of the fundamental tasks in computer vision. Many supervised
methods, including recently proposed Convolutional Neural Networks (CNN)-based …

In this paper, we propose a novel color constancy approach, called Bag of Color Features
(BoCF), building upon Bag-of-Features pooling. The proposed method substantially reduces …

Color constancy is an essential part of the Image Signal Processor (ISP) pipeline, which
removes the color bias of the captured image generated by scene illumination. Recently …

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 …