Captured images are usually influenced by fog or haze. In reality, image dehazing is challenging. This paper proposes a modified artificial multiple-exposure image fusion (AMEF) algorithm to remove the haze from an image. In the algorithm, first, an adaptive gamma-correction transform with the mean and standard deviation values of each component of a hazy image is utilized to verify the intensities. Second, the homomorphic filtering algorithm is introduced into the Gaussian pyramid and Laplacian pyramid to compute the exposed accessible images. Last, a modified Laplacian filter method is presented to calculate the contrast of the exposed accessible images. Further, extensive experimental results demonstrate that the proposed algorithm has superior performance compared with that of some state-of-the-art methods, including higher contrast, richer details and a better visual effect in the dehazed image.

中文翻译：

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一种通过自适应伽玛校正和修正 AMEF 的新型图像去雾算法

捕获的图像通常会受到雾或霾的影响。实际上，图像去雾是具有挑战性的。本文提出了一种改进的人工多重曝光图像融合（AMEF）算法来去除图像中的雾霾。在该算法中，首先，利用具有模糊图像每个分量的平均值和标准偏差值的自适应伽马校正变换来验证强度。其次，在高斯金字塔和拉普拉斯金字塔中引入同态滤波算法来计算暴露的可访问图像。最后，提出了一种改进的拉普拉斯滤波器方法来计算暴露的可访问图像的对比度。此外，大量的实验结果表明，与一些最先进的方法相比，所提出的算法具有更优越的性能，包括更高的对比度、