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Single Image Defogging Based on Illumination Decomposition for Visual Maritime Surveillance

机译:基于视觉海上监控照明分解的唯一图像缺点

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Single image fog removal is important for surveillance applications, and, recently, many defogging methods have been proposed. Due to the adverse atmospheric conditions, the scattering properties of foggy images depend on not only the depth information of scene but also the atmospheric aerosol model, which has a more prominent influence on illumination in a fog scene than that in a haze scene. However, the recent defogging methods confuse haze and fog, and they fail to consider fully the scattering properties. Thus, these methods are not sufficient to remove fog effects, especially for images in maritime surveillance. Therefore, this paper proposes a single image defogging method for visual maritime surveillance. First, a comprehensive scattering model is proposed to formulate a fog image in the glow-shaped environmental illumination. Then, an illumination decomposition algorithm is proposed to eliminate the glow effect on the airlight radiance and recover a fog layer, in which the objects at the infinite distance have uniform luminance. Second, a transmission-map estimation based on the non-local haze-lines prior is utilized to constrain the transmission map into a reasonable range for the input fog image. Finally, the proposed illumination compensation algorithm enables the defogging image to preserve the natural illumination information of the input image. In addition, a fog image dataset is established for the visual maritime surveillance. The experimental results based on the established dataset demonstrate that the proposed method can outperform the state-of-the-art methods in terms of both the subjective and objective evaluation criteria. Moreover, the proposed method can effectively remove fog and maintain naturalness for fog images.
机译:单幅图像雾移除对于监控应用很重要,而最近,已经提出了许多缺失方法。由于不良大气条件,雾图像的散射特性不仅取决于场景的深度信息,而且依赖于大气气溶胶模型,这对雾场景中的照明具有比较突出的影响。然而,最近的缺失方法混淆了雾霾和雾,并且它们未能完全考虑散射特性。因此,这些方法不足以去除雾效应,尤其是用于海上监测的图像。因此,本文提出了一种用于视觉海上监测的单个图像缺点方法。首先,提出了一种全面的散射模型来制定雾化环境照明中的雾图像。然后,提出了一种照明分解算法以消除对机灯辐射的辉光效应并恢复雾层,其中无限距离处的物体具有均匀的亮度。其次,利用基于非局部雾线线的传输地图估计来将传输映射限制为输入雾图像的合理范围。最后,所提出的照明补偿算法使得Defogging图像能够保留输入图像的自然照明信息。此外,为视觉海上监控建立了雾图像数据集。基于已建立的数据集的实验结果表明,所提出的方法可以在主观和客观评估标准方面优于最先进的方法。此外,所提出的方法可以有效地去除雾并保持雾图像的自然度。

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