Illuminant estimation for color constancy: why spatial-domain methods work and the role of the color distribution

Abstract

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. In this work, we distinguish methods depending on whether they work directly from color values (i.e., color domain) or from values obtained from the image's spatial information (e.g., image gradients/frequencies). We show that spatial information does not provide any additional information that cannot be obtained directly from the color distribution and that the indirect aim of spatial-domain methods is to obtain large color differences for estimating the illumination direction. This finding allows us to develop a simple and efficient illumination estimation method that chooses bright and dark pixels using a projection distance in the color distribution and then applies principal component analysis to estimate the illumination direction. Our method gives state-of-the-art results on existing public color constancy datasets as well as on our newly collected dataset (NUS dataset) containing 1736 images from eight different high-end consumer cameras.

RAW Image Reconstruction Using a Self-contained sRGB–JPEG Image with Small Memory Overhead

“…We note that we have modified their approach to use the recent state-of-the-art method proposed by Ferstl et al (2013) to perform the image upsampling. Images used in this paper were taken from various online data sets that contain RAW-sRGB pairs, including images from Kim et al (2012), Cheng et al (2014), Nguyen et al (2014), andDang-Nguyen et al (2015).…”

Practical automatic background substitution for live video

“…A major assumption in these approaches is that the original background is similar to the new background, which we cannot guarantee in our application. The third category of methods is based on color constancy, estimating the illumination of the image first and then adjusting colors accordingly [19][20][21][22]. In this paper, we utilize the most basic and popular color constancy method, the white-patch algorithm [25], to estimate the light source color, since we need its efficiency for real-time application.…”

“…Some seamless image composition techniques [17,18] may seem relevant at first glance, but they require the original and new backgrounds to be similar. Other color correction techniques based on color constancy [19][20][21][22] are more suitable in our context. Color constancy methods first estimate the light source color of the image, and then adjust pixel colors according to the specified hypothetical light source color.…”

Integrated Saturation Weighting based Color Cat Algorithm

“…Some of such methods makes use of simple linear or perhaps non-linear power level transformation functions, whereas other people use difficult analysis regarding different photograph features including the edge and connected component information. Contrast development problem throughout digital images may be resolved employing various techniques, but Histogram Equalization (HE) [8] technique will be the widely employed one. Histogram Equalization approach flattens your histogram and stretches your dynamic array of intensity values when using the cumulative thickness function.…”