This paper presents SuPeR-B, a novel, Retinex inspired colorspatialalgorithm to enhance images acquired under difficult light conditions, such as pictures containing dark and bright regions caused by backlight and/o...
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(纸本)9789897584886
This paper presents SuPeR-B, a novel, Retinex inspired colorspatialalgorithm to enhance images acquired under difficult light conditions, such as pictures containing dark and bright regions caused by backlight and/or local, not diffused spotlight. SuPeR-B takes as input a color image and improves its readability by processing its color channels independently in accordance with some principles of the Retinex theory. Precisely, SuPeR-B re-works the channel intensity of each pixels accounting for differences computed both in the spatial and intensity domains. In this way, SuPeR-B acts as a bilater filter. The experiments, carried out on a real-world dataset, shows that SuPeR-B ensures good enhancement results, also in comparison with other state-of-the-art algorithms: SuPeR-B improves the overall content of the image, making the dark regions brighter and more contrasted, while lowering possible chromatic dominants of the light.
The original presentation of Retinex, a spatialcolor 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...
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The original presentation of Retinex, a spatialcolor 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. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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