Avoiding the Deconvolution: Framework Oriented Color Transfer for Enhancing Low-Light Images

Laura Florea, Corneliu Florea, Ciprian Ionascu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016, pp. 27-35

Abstract


In this paper we introduce a novel color transfer method to address the underexposed image amplification problem. Targeted scenario implies a dual acquisition, containing a normally exposed, possibly blurred, image and an underexposed/low-light but sharp one. The problem of enhancing the low-light image is addressed as a color transfer problem. To properly solve the color transfer, the scene is split into perceptual frameworks and we propose a novel piece-wise approximation. The proposed method is shown to lead to robust results from both an objective and a subjective point of view.

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[bibtex]
@InProceedings{Florea_2016_CVPR_Workshops,
author = {Florea, Laura and Florea, Corneliu and Ionascu, Ciprian},
title = {Avoiding the Deconvolution: Framework Oriented Color Transfer for Enhancing Low-Light Images},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2016}
}