The visibility of an image captured in poor weather (such as haze, fog, mist, smog) degrades due to scattering of light by atmospheric particles. Single image dehazing (SID) methods are used to restore visibility from a single hazy image. The SID is a challenging problem due to its ill-posed nature. Typically, the atmospheric scattering model (ATSM) is used to solve SID problem. The transmission and atmospheric light are two prime parameters of ATSM. The accuracy and effectiveness of SID depends on accurate value of transmission and atmospheric light. The proposed method translates transmission estimation problem into estimation of the difference between minimum color channel of hazy and haze-free image. The translated problem presents a lower bound on transmission and is used to minimize reconstruction error in dehazing. The lower bound depends upon the bounding function (BF) and a quality control parameter. A non-linear model is then proposed to estimate BF for accurate estimation of transmission. The proposed quality control parameter can be utilized to tune the effect of dehazing. The accuracy obtained by the proposed method for transmission is compared with state of the art dehazing methods. Visual comparison of dehazed images and objective evaluation further validates the effectiveness of the proposed method.

中文翻译：

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单图像去雾中使用非线性边界函数的透射率下界


由于大气颗粒对光的散射，在恶劣天气（例如霾、雾、薄雾、烟雾）下拍摄的图像的可见度会降低。单图像去雾 (SID) 方法用于恢复单个模糊图像的可见性。由于其不适定性质，SID 是一个具有挑战性的问题。通常，大气散射模型（ATSM）用于解决 SID 问题。传输和大气光是 ATSM 的两个主要参数。 SID的准确性和有效性取决于传输和大气光的准确值。所提出的方法将传输估计问题转化为有雾图像和无雾图像的最小颜色通道之间的差异的估计。转换后的问题提出了传输的下限，并用于最小化去雾中的重建误差。下限取决于边界函数 (BF) 和质量控制参数。然后提出一个非线性模型来估计 BF，以准确估计传输。所提出的质量控制参数可用于调整去雾效果。将所提出的传输方法获得的精度与最先进的去雾方法进行比较。去雾图像的视觉比较和客观评价进一步验证了该方法的有效性。