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Several different implementations of the Retinex model have been derived from the original Land and McCann's paper. This paper aims at presenting the Milano-Retinex family, a collection of slightly different Retinex implementations, developed by the Department of Computer Science of Universitá degli Studi di Milano. One important difference is in their goals: while the original Retinex aims at modeling vision, the Milano-Retinex family is mainly applied as an image enhancer, mimicking some mechanisms of the human vision system.

Abstract-In this paper, we present a segmentation technique which joins a multi-scale texture based approach and a fuzzy segmentation method using the color gradient of Di Zenzo. Thus maps of homogeneous texture patterns are enhanced by edge localization. A topographic distance is used to calculate membership degrees to each region. Both lead to segmentation using a step of watershed flooding, with few parameters to set. Moreover computation complexity has been reduced to allow treatments of images in full size and colors. Index Terms-color image segmentation, fuzzy image segmentation, color watershed, color gradient, multi-scale texture segmentation

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In this paper, we present an efficient approach to digital color restoration, based on the idea of recovering the appearance of color rather than the original color signal, since, in most of the cases, for old films the original reference is missing, and new films or digital coding can be subject to severe gamut transformations. This approach is based on the application of algorithms inspired by the capabilities of the Human Vision System of automatically adjust to the variation of color and lightness in the scene. The proposed method allows more unsupervised restoration. We present an overview of the approach, characteristics of this family of algorithms, and restoration examples.