A novel algorithm for color constancy
International Journal of Computer Vision
Color by Correlation: A Simple, Unifying Framework for Color Constancy
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new algorithm for unsupervised global and local color correction
Pattern Recognition Letters - Special issue: Colour image processing and analysis
ACM SIGGRAPH 2006 Papers
A perturbed particle swarm algorithm for numerical optimization
Applied Soft Computing
Image thresholding based on Pareto multiobjective optimization
Engineering Applications of Artificial Intelligence
Pattern Recognition Letters
A multiobjective approach to MR brain image segmentation
Applied Soft Computing
Color Constancy Using Natural Image Statistics and Scene Semantics
IEEE Transactions on Pattern Analysis and Machine Intelligence
SAR image segmentation based on Artificial Bee Colony algorithm
Applied Soft Computing
High dynamic range optimal fuzzy color image enhancement using Artificial Ant Colony System
Applied Soft Computing
Robust automatic white balance algorithm using gray color points in images
IEEE Transactions on Consumer Electronics
Improving gamut mapping color constancy
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A comparison of computational color constancy Algorithms. II. Experiments with image data
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Vision Processing for Realtime 3-D Data Acquisition Based on Coded Structured Light
IEEE Transactions on Image Processing
Improving Color Constancy Using Indoor–Outdoor Image Classification
IEEE Transactions on Image Processing
HPCC '12 Proceedings of the 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems
Image contrast enhancement for preserving mean brightness without losing image features
Engineering Applications of Artificial Intelligence
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Color images captured under various environments are often not ready to deliver the desired quality due to adverse effects caused by uncontrollable illumination settings. In particular, when the illuminate color is not known a priori, the colors of the objects may not be faithfully reproduced and thus impose difficulties in subsequent image processing operations. Color correction thus becomes a very important pre-processing procedure where the goal is to produce an image as if it is captured under uniform chromatic illumination. On the other hand, conventional color correction algorithms using linear gain adjustments focus only on color manipulations and may not convey the maximum information contained in the image. This challenge can be posed as a multi-objective optimization problem that simultaneously corrects the undesirable effect of illumination color cast while recovering the information conveyed from the scene. A variation of the particle swarm optimization algorithm is further developed in the multi-objective optimization perspective that results in a solution achieving a desirable color balance and an adequate delivery of information. Experiments are conducted using a collection of color images of natural objects that were captured under different lighting conditions. Results have shown that the proposed method is capable of delivering images with higher quality.