Milano Retinex family

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 Universit\ue1 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

QBRIX : a quantile-based approach to retinex

In this paper, we introduce a novel probabilistic version of retinex. It is based on a probabilistic formalization of the random spray retinex sampling and contributes to the investigation of the spatial properties of the model. Various versions available of the retinex algorithm are characterized by different procedures for exploring the image content (so as to obtain, for each pixel, a reference white value), then used to rescale the pixel lightness. Here we propose an alternative procedure, which computes the reference white value from the percentile values of the pixel population. We formalize two versions of the algorithm: one with global and one with local behavior, characterized by different computational costs

Perceptually inspired HDR images tone mapping with color correction

In this paper we present a novel Tone Mapping Operator (TMO) for High Dynamic Range (HDR) images. Starting from an algorithm for low dynamic range image enhancement and color correction called ACE (Automatic Color Enhancement); we keep its differential and local behavior, introducing new features to correctly handle the high variation of HDR images. In particular, we add a non-linear local regulator able to automatically tune the algorithm parameters on image variations. In this way, the algorithm behavior changes according to local variations. Moreover, a key setting feature has been added to control the output appearance; it automatically proposes an appropriate key value for the final spatial invariant display mapping. The proposed method performs the spatial variant filtering using only one parameter that tunes output detail visibility versus overall contrast. We propose a default setting that guarantees a good solution in most cases. Test, results and comparison are presented