Abstract
Uneven illumination is a recurrent problem in image processing. This is essentially due to image acquisition sensors’ malfunction or external interference. In this paper we propose a variational model for nonuniform illumination correction, that incorporates a penalty term that performs the intensity distribution transfer between two pre-defined sub-regions of the input scalar image, one uniformly illuminated and the other nonuniformly illuminated. This term representing the illumination correction is a Wasserstein distance. It corresponds to the optimal permutation minimizing the cost of rearranging the intensity distribution of the nonuniformly illuminated sub-region into the other, the uniformly illuminated. Simultaneously, this variational model also carries out a regularization of the image by means of a total variation penalty term, to reduce noise. The effectiveness of the model is illustrated for some images.
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Acknowledgements
This work was partially supported by the Centre for Mathematics of the University of Coimbra – UID/MAT/00324/2013, funded by the Portuguese Government through FCT/MCTES and co-funded by the European Regional Development Fund through the Partnership Agreement PT2020. Luís Pinto was also supported by FCT scholarship SFRH/BPD/112687/2015.
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Figueiredo, I.N., Pinto, L., Gonçalves, G., Engquist, B. (2018). A Variational Model for Image Artifact Correction Based on Wasserstein Distance. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_5
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DOI: https://doi.org/10.1007/978-3-319-68195-5_5
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