Restoring Edge and Color using Weighted Near-Infrared Image and Color Transmission Maps for Robust Haze Removal

Onhi Kato, Akira Kubota
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Abstract

In recent years, various haze removal methods based on atmospheric scattering models have been proposed. Most methods target strong haze images in which light is scattered equally in all color channels. This paper proposes a haze removal method using near-infrared (NIR) images for weak haze images. The proposed method first restores the edges of color images by fusing weighted NIR images. Second, it estimates transmission maps for all color channels based on a wavelength-dependent scattering model and restores the color of the edge-restored image using the estimated transmission maps. Finally, the edge- restored and color-restored images are blended. Qualitative and quantitative evaluations demonstrate that the proposed method can restore edges and colors more naturally in weak haze images than conventional methods.
使用加权近红外图像和彩色传输图恢复边缘和颜色,用于鲁棒去除雾霾
近年来,人们提出了各种基于大气散射模型的雾霾去除方法。大多数方法针对强雾霾图像,其中光在所有颜色通道中均匀散射。针对弱雾图像,提出了一种利用近红外(NIR)图像去雾的方法。该方法首先通过融合加权近红外图像恢复彩色图像的边缘;其次,基于波长相关的散射模型估计所有颜色通道的传输映射,并使用估计的传输映射恢复边缘恢复图像的颜色。最后,对边缘恢复图像和彩色恢复图像进行混合处理。定性和定量评价表明,与传统方法相比,该方法可以更自然地恢复弱雾图像的边缘和颜色。
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