A Retinex Inspired Bilateral Filter for Enhancing Images under Difficult Light Conditions

This paper presents SuPeR-B, a novel, Retinex inspired color spatial algorithm 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.