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Evaluates dehazing algorithm performance using a new RGB/NIR data set, suggesting better image enhancement outcomes.
Realistic test data is needed to evaluate and rank the performance and quality of dehazing algorithms for image enhancement. Especially for professional photography and cinematography, this test data has to fulfill high quality standards including high dynamic range, sufficient resolution and natural color reproduction. For this purpose, we present a new multispectral data set that includes RGB and near-infrared (NIR) images captured by two professional digital motion picture cameras. Compared to existing data sets, the benefits of our set are threefold. Due to our two camera setting we are able to provide synchronous and well registered RGB/NIR image pairs captured at the same instant of time. High quality real image sequences allow future algorithms to take account of the temporal consistency of the dehazed output images. Furthermore, to facilitate a uniform and fair evaluation of different algorithms we provide ground truth images for selected RGB/NIR image pairs. The data set is freely available at http://www.arri.com/innovations/.
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Lüthen et al. (2017) studied this question.
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