Raikwar Suresh Chandra, Tapaswi Shashikala
IEEE Trans Image Process. 2020 Feb 28. doi: 10.1109/TIP.2020.2975909.
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.
在恶劣天气(如薄雾、浓雾、霭、烟雾)下拍摄的图像,其能见度会因大气粒子对光的散射而降低。单图像去雾(SID)方法用于从单个模糊图像中恢复能见度。由于其不适定的性质,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。透射率和大气光强是ATSM的两个主要参数。SID的准确性和有效性取决于透射率和大气光强的准确值。所提出的方法将透射率估计问题转化为模糊图像和无雾图像的最小颜色通道之间差异的估计。转化后的问题给出了透射率的下限,并用于最小化去雾中的重建误差。下限取决于边界函数(BF)和一个质量控制参数。然后提出了一个非线性模型来估计BF,以准确估计透射率。所提出的质量控制参数可用于调整去雾效果。将所提出方法获得的透射率准确性与现有去雾方法进行比较。去雾图像的视觉比较和客观评估进一步验证了所提出方法的有效性。