Colour in Context
Research group Computer Vision Center |
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Image Compression The aim of this work is to apply perceptual concepts to defina a perceptual pre-quantizer in order to improve image compression algorithms. | Related publications |
Color Feature Detection for Object Recognition Luminance edges are still the main source of information in the state-of-the-art methods for feature detection. We propose to exploit the statistical structure of luminance and color in natural images to extract the most discriminative features from the viewpoint of information theory for object recognition. | Related publications |
Chromatic Induction We propose a computational model that reprodce chromatic induction processes unifying chromatic assimilation and chromatic contrast into a single perceptual process. | Related publications |
High Dynamic Range We try to perform a High Dynamic Range compression of color images using perceptual criterias. | Related publications |
Parametric model for Color Naming A full parametric model has been defined on the CIE lab space. Each of the 11 basic colour categories is modelled with a fuzzy set characterized by a combination of sigmoids as membership functions. | Related publications |