I-HAZE: a Dehazing Benchmark with Real Hazy and Haze-free Indoor Images
(2018) 19th International Conference on Advanced Concepts for Intelligent Vision Systems — Location: Poitiers, France (24.September.2018)
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- Abstract
- Image dehazing has become an important computational imaging topic in the recent years. However, due to the lack of ground truth images, the comparison of dehazing methods is not straightfor- ward, nor objective. To overcome this issue we introduce I-HAZE, a new dataset that contains 35 image pairs of hazy and corresponding haze-free (ground-truth) indoor images. Different from most of the existing dehaz- ing databases, hazy images have been generated using real haze produced by a professional haze machine. To ease color calibration and improve the assessment of dehazing algorithms, each scene includes a MacBeth color checker. Moreover, since the images are captured in a controlled environment, both haze-free and hazy images are captured under the same illumination conditions. This represents an important advantage of the I-HAZE dataset that allows us to objectively compare the existing image dehazing techniques using traditional image quality metrics such as PSNR and SSIM.
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Citations
Cosmin Ancuti, Codruta Ancuti, Radu Timofte, & De Vleeschouwer, C. (2018). I-HAZE: a Dehazing Benchmark with Real Hazy and Haze-free Indoor Images. Advanced Concepts for Intelligent Vision Systems. Published. 19th International Conference on Advanced Concepts for Intelligent Vision Systems, Poitiers, France. https://doi.org/10.48550/arXiv.1804.05091