A Multi-Scale Adaptive Grey World Algorithm

Abstract

Grey world algorithm is a well-known color constancy algorithm. It is based on the Grey-World assumption i.e., the average reflectance of surfaces in the world is achromatic. This algorithm is simple and has low computational costs. However, for the images with several colors, the light source color could not be estimated correctly using the Grey World algorithm. In this paper, we propose a Multi-scale Adaptive Grey World algorithm (MAGW). First, multi-scale images are obtained based on wavelet transformation and the illumination color is estimated from different scales images. Then according to the estimated illumination color, the original image is mapped into the image under a canonical illumination with supervision of an adaptive reliability function, which is based on the image entropy. The experimental results show that our algorithm is effective and also has low computational costs.