A Hybrid L1-L0 Layer Decomposition Model for Tone Mapping

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The code in this package implements the tone mapping method as described in the following paper: “A Hybrid L1-L0 Layer Decomposition Model for Tone Mapping”.

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Authors Z. Liang, J. Xu, D. Zhang, Z. Cao and L. Zhang
Journal/Conference Name Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Paper Category
Paper Abstract Tone mapping aims to reproduce a standard dynamic range image from a high dynamic range image with visual information preserved. State-of-the-art tone mapping algorithms mostly decompose an image into a base layer and a detail layer, and process them accordingly. These methods may have problems of halo artifacts and over-enhancement,due to the lack of proper priors imposed on the two layers. In this paper, we propose a hybrid l_1-l_0 decomposition model to address these problems. Specifically, an l_1 sparsity term is imposed on the base layer to model its piecewise smoothness property. An l_0 sparsity term is imposed on the detail layer as a structural prior, which leads to piecewise constant effect. We further propose a multiscale tone mapping scheme based on our layer decomposition model. Experiments show that our tone mapping algorithm achieves visually compelling results with little halo artifacts, outperforming the state-of-the-art tone mapping algorithms in both subjective and objective evaluations.
Date of publication 2018
Code Programming Language MATLAB
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