Results 11 to 20 of about 3,709,095 (175)
Rehabilitating the Color Checker Dataset for Illuminant Estimation [PDF]
Color and Imaging Conference, 2018 In a previous work, it was shown that there is a curious problem with the benchmark ColorChecker dataset for illuminant estimation. To wit, this dataset has at least 3 different sets of ground-truths.
Ghalia Hemrit +5 more
semanticscholar +8 more sources
The bright-chromagenic algorithm for illuminant estimation [PDF]
Color and Imaging Conference, 2007 This article proposes a new algorithm for illuminant estimation based on the concept of chromagenic color constancy, where two pictures are taken from each scene: A normal one and one where a colored filter is placed in front of the camera. The basic formulation of the chromagenic algorithm has inherent weaknesses, namely, a need for perfectly ...
Fredembach, Clément, Finlayson, Graham
core +15 more sources
Gamut Constrained Illuminant Estimation [PDF]
International Journal of Computer Vision, 2003 This paper presents a novel solution to the illuminant estimation problem: the problem of how, given an image of a scene taken under an unknown illuminant, we can recover an estimate of that light. The work is founded on previous gamut mapping solutions to the problem which solve for a scene illuminant by determining the set of diagonal mappings which ...
Finlayson, Graham +2 more
core +6 more sources
Illuminant spectrum estimation at a pixel [PDF]
Journal of the Optical Society of America A, 2011 In this paper, an algorithm is proposed to estimate the spectral power distribution of a light source at a pixel. The first step of the algorithm is forming a two-dimensional illuminant invariant chromaticity space. In estimating the illuminant spectrum, generalized inverse estimation and Wiener estimation methods were applied.
Sivalogeswaran, Ratnasingam +1 more
openaire +3 more sources
The Cube++ Illumination Estimation Dataset
IEEE Access, 2020 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 pipelines of most digital cameras.
Egor Ershov +8 more
doaj +5 more sources
Illuminant estimation in multispectral imaging. [PDF]
Journal of the Optical Society of America A, 2017 With the advancement in sensor technology, the use of multispectral imaging is gaining wide popularity for computer vision applications. Multispectral imaging is used to achieve better discrimination between the radiance spectra, as compared to the color images. However, it is still sensitive to illumination changes.
Haris Ahmad Khan +3 more
semanticscholar +4 more sources
Providing a Single Ground-Truth for Illuminant Estimation for the ColorChecker Dataset
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 The ColorChecker dataset is one of the most widely used image sets for evaluating and ranking illuminant estimation algorithms. However, this single set of images has at least 3 different sets of ground-truth (i.e., correct answers) associated with it ...
Simone Bianco +2 more
exaly +2 more sources
When the brightest is not the best: illuminant estimation from the geometry of specular highlights
bioRxivColour constancy supports stable object-colour perception across changes in illumination. Illuminant colour can be inferred from white surfaces or specular highlights, and many models adopt a “brightest is white” heuristic to identify illuminant colour ...
Morimoto T, Lee RJ, Smithson HE.
europepmc +2 more sources
Illuminant color estimation for real-world mixed-illuminant scenes [PDF]
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011 We present a physics-based approach for illuminant color estimation of arbitrary images, which is explicitly designed for handling images with multiple illuminants. The majority of techniques that extract the illuminant color assume that the illumination is constant across the scene. This, however, is not often the case.
Christian Riess +2 more
openaire +3 more sources
Deep reinforcement learning-based patch selection for illuminant estimation [PDF]
Image and Vision Computing, 2019 Previous deep learning based approaches to illuminant estimation either resized the raw image to lower resolution or randomly cropped image patches for the deep learning model.
Bolei Xu +4 more
semanticscholar +2 more sources