Abstract
An automatic natural scenes classifier and enhancer is presented. It works mainly by combining chromatic and positional criterions in order to classify and enhance portraits and landscapes natural scenes images. Various image processing applications can easily take advantage from the proposed solution, e.g. automatically drive camera settings for the optimization of exposure, focus, or shutter speed parameters, or post processing applications for color rendition optimization. A large database of high quality images has been used to design and tune the algorithm, according to wide accepted assumptions that few chromatic classes on natural images have the most perceptive impact on the human visual system. These are essentially skin, vegetation and sky?sea. The adaptive color rendition technique, which has been derived from the results produced by the image classifier, is based on a simple yet effective principle: it shifts the chromaticity of the regions of interest towards the statistically expected ones. Introduction of disturbing color artifacts is avoided by a proper modulation and by preservation of original image luminance values. Quantitative results obtained over an extended data set not belonging to the training database, show the effectiveness of the solution proposed both for the natural image classification and the color enhancement techniques.
Published Version
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