Abstract
The original presentation of Retinex, a spatial color correction and image enhancement algorithm modeling the human vision system, as proposed by Land and McCann in 1964, uses paths to explore the image in search of a local reference white point. The interesting results of this algorithm have led to the development of many versions of Retinex. They follow the same principle but differ in the way they explore the image, with, for example, random paths, random samples, convolution masks, and variational formulations. We propose an alternative way to explore local properties of Retinex, replacing random paths by traces of a specialized swarm of termites. In presenting the spatial characteristics of the proposed method, we discuss differences in path exploration with other Retinex implementations. Experiments, results, and comparisons are presented to test the efficacy of the proposed Retinex implementation.
Highlights
During the past decades a significant amount of research has been undertaken to understand human visual perception, which is not a trivial task as the human visual system (HVS) has complex and robust mechanisms to acquire useful information from the environment
In order to deal with this locality in image appearance, different image processing methods and frameworks have been developed with the intent to exhibit behaviors similar to the HVS, such as Automatic Color Equalization (ACE),[1] Spatio-Temporal Retinex-inspired (STRESS),[2] image Color Appearance Model, and its evolutions,[3,4] and the various Retinex implementations, which are the interest of this work
We propose a new implementation of Retinex, following the approach of the first group, in particular substituting the Brownian paths with a so-called termite colony exploration of the image, a diversified and tuned model for image processing derived from the ant colony system (ACS) for traveling salesman problem (TSP)
Summary
During the past decades a significant amount of research has been undertaken to understand human visual perception, which is not a trivial task as the human visual system (HVS) has complex and robust mechanisms to acquire useful information from the environment. The original Retinex model of lightness and color perception was proposed by Land and McCann about 50 years ago.[5,6] In the light of current developments, there has been a renewed interest in color appearance.[7,8] The principal assumption of the Retinex theory is that the sensation of color comes from a comparison among the various areas in the scene In this comparison performed separately on each of the three color channels, a series of ratios and products among the various parts of the image are computed to calculate each pixel appearance. We propose a new implementation of Retinex, following the approach of the first group, in particular substituting the Brownian paths with a so-called termite colony exploration of the image, a diversified and tuned model for image processing derived from the ACS for traveling salesman problem (TSP).
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