Abstract
In the present article we focus on enhancing the contrast of images with low illumination that present large underexposed regions. Most of these images represent night images. When applying standard contrast enhancement techniques, usually the night mood is modified, and also a noise over-enhancement within the darker regions is introduced. In a previous work we have described our local contrast correction algorithm designed to enhance images where both underexposed and overexposed regions are simoultaneously present. Here we show how this algorithm is able to automatically enhance night images, preserving the original mood. To further improve the performance of our method we also propose here a denoising procedure where the strength of the smoothing is a function of an estimated level of noise and it is further weighted by a saliency map. The method has been applied to a proper database of outdoor and indoor underexposed images. Our results have been qualitatively compared with well know contrast correction methods.
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Corchs, S., Gasparini, F. (2011). Enhancing Underexposed Images Preserving the Original Mood. In: Schettini, R., Tominaga, S., Trémeau, A. (eds) Computational Color Imaging. CCIW 2011. Lecture Notes in Computer Science, vol 6626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20404-3_10
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DOI: https://doi.org/10.1007/978-3-642-20404-3_10
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