The human visual system unconsciously determines the color of the objects by “discounting”
the effects of the illumination, whereas machine vision systems have difficulty performing this …

We introduce a convolutional framework (CF) for computational color constancy, building
upon the established low-level image feature-based framework, which utilized simple image …

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 …

Current multi-illumination color constancy methods typically estimate illumination for each
pixel directly. However, according to the multi-illumination imaging equation, the color of …

Our visual system unconsciously estimates the objects reflectance in the scene. Even under
different illumination conditions, it can discount the effects of the illuminant to recognize the …

Hyperspectral imaging (HSI) is emerging as a promising novel imaging modality with
various potential surgical applications. Currently available cameras, however, suffer from …

In recent studies, alongside introducing new approaches for color constancy, we have also
focused on improving existing techniques and introducing new perspectives. Our motivation …

The classical color constancy algorithms concentrate only on the color of a grey surface to
estimate the light color and to white balance the image. In this paper, we show that the …

Generative adversarial network (GAN) has attracted extensive attention in color constancy
because it allows pixel-wise supervision. However, the misinterpretation of color features …

Illumination estimation refers to estimating the chromaticity vector of illumination, and can be
used to recover the surface color under white light. Dual-illuminant is a common scenario in …