This paper focuses on correcting a camera image that has been improperly white-balanced.
This situation occurs when a camera's auto white balance fails or when the wrong manual …

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 …

While modern deep neural networks (DNNs) achieve state-of-the-art results for illuminant
estimation, it is currently necessary to train a separate DNN for each type of camera sensor …

Background and objective Dermatological images are typically diagnosed based on visual
analysis of the skin lesion acquired using a dermoscope. However, the final quality of the …

In this paper, we describe a new large dataset for illumination estimation. This dataset,
called INTEL-TAU, contains 7022 images in total, which makes it the largest available high …

Annotated datasets for automatic white balance (AWB) are used for the evaluation and,
when necessary, the training, of AWB methods. Relying on such datasets requires …

Computational color constancy has the important task of reducing the influence of the scene
illumination on the object colors. As such, it is an essential part of the image processing …

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 …

In this paper, we study the importance of pretraining for the generalization capability in the
color constancy problem. We propose two novel approaches based on convolutional …

Multi-illuminant-based color constancy (MCC) is quite a challenging task. In this paper, we
proposed a novel model motivated by the bottom-up and top-down mechanisms of human …