Speed-up Technique for a Local Automatic Colour Equalization Model

In this paper we propose a speed‐up technique for a local automatic colour equalization operator derived from a model of the human vision system. This method is characterized by local and global filtering effects, that simultaneously achieve different equalization tasks e.g. performing colour and lightness constancy, realizing dynamic image data driven stretching, controlling the contrast. We describe a way to quickly create a filtering mapping function to perform the global component of the mapping. This method is based on singular value decomposition (SVD) applied to sampled and filtered points in the input image. Then, the local information is added computing the basic algorithm on a neighbourhood of each input pixel. A slight quality loss is the price that we have to pay for a speed‐up of more than two orders of magnitude of the basic algorithm. We present the results on several images and discuss the efficiency and the drawbacks of the speed‐up technique.