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A Spectral Hazy Image Database

机译:光谱模糊图像数据库

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摘要

We introduce a new database to promote visibility enhancement techniques intended for spectral image dehazing. SHIA (Spectral Hazy Image database for Assessment) is composed of two real indoor scenes Ml and M2 of 10 levels of fog each and their corresponding fog-free (ground-truth) images, taken in the visible and the near infrared ranges every 10 nm starting from 450 to 1000 nm. The number of images that form SHIA is 1540 with a size of 1312 × 1082 pixels. All images are captured under the same illumination conditions. Three of the well-known dehazing image methods based on different approaches were adjusted and applied on the spectral foggy images. This study confirms once again a strong dependency between dehazing methods and fog densities. It urges the design of spectral-based image dehazing able to handle simultaneously the accurate estimation of the parameters of the visibility degradation model and the limitation of artifacts and post-dehazing noise.
机译:我们引入了一个新的数据库,以促进用于光谱图像去雾的能见度增强技术。 SHIA(用于评估的光谱模糊图像数据库)由两个真实的室内场景M1和M2组成,每个场景具有10个雾度,并在每10 nm的可见光和近红外范围内拍摄相应的无雾(真实)图像从450到1000 nm形成SHIA的图像数量为1540,尺寸为1312×1082像素。在相同的照明条件下捕获所有图像。调整了基于不同方法的三种著名的除雾图像方法,并将其应用于光谱雾图像。这项研究再次证实了除雾方法和雾浓度之间的强烈依赖性。它敦促基于光谱的图像去雾设计能够同时处理可视性降级模型参数的精确估计以及伪影和去雾后噪声的限制。

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