Image Annotation for Adaptive Enhancement of Uncalibrated Color Images

The paper describes an innovative image annotation tool, based on a multi-class Support Vector Machine, for classifying image pixels in one of seven classes – sky, skin, vegetation, snow, water, ground, and man-made structures – or as unknown. These visual categories mirror high-level human perception, permitting the design of intuitive and effective color and contrast enhancement strategies. As a pre-processing step, a smart color balancing algorithm is applied, making the overall procedure suitable for uncalibrated images, such as images acquired by unknown systems under unknown lighting conditions.

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