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Perceptual contrast enhancement of dark images based on textural coefficients

机译:基于纹理系数的暗图像感知对比度增强

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We propose perceptual contrast enhancement of dark images based on textural coefficients. The textural coefficient indicates textural degree of intensity and adaptively stretches the dynamic range in an image. First, we calculate gray level difference between a central pixel and its adjacent ones. Because some differences are obviously noticeable by human eyes, we only use unnoticeable differences to obtain the textural coefficient. We apply the just noticeable difference (JND) of the human visual system (HVS) to obtain the proper threshold. Then, we apply a Gaussian kernel to texture coefficients for avoiding excessive differences between adjacent ones. Finally, we perform optimal contrast tone mapping to obtain a mapping function. Experimental results show that the proposed method successfully enhances dark regions while avoiding over-enhancement in bright regions without halo artifact and tone distortion.
机译:我们提出了基于纹理系数的暗图像的感知对比度。纹理系数表示纹理的强度,并自适应地拉伸图像中的动态范围。首先,我们计算中心像素和相邻的灰度差。由于人眼显然有些差异显然,我们只使用不明显的差异来获得纹理系数。我们应用人类视觉系统(HVS)的刚刚明显的差异(JND)以获得适当的阈值。然后,我们将高斯内核应用于纹理系数,以避免相邻之间的过度差异。最后,我们执行最佳对比度映射以获得映射函数。实验结果表明,该方法成功增强了暗区,同时避免了明亮地区的过度增强而没有晕圈伪影和音调变形。

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