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Dehaze Enhancement Algorithm Based on Retinex Theory for Aerial Images Combined with Dark Channel

机译:基于Retinex理论的空中图像与暗通道相结合的去吸收增强算法

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In order to improve the visual effect of aerial images in foggy weather, a Retinex defogging algorithm combining dark channel priors is proposed to solve the phenomenon of insufficient defogging and over-enhancement of aerial defogging in Reinex defogging. First, the foggy original image is decomposed into foggy incident light components and foggy reflected light components by Retinex theory. Then, the principle of foggy image degradation is analyzed by an atmospheric scattering model, and the dark channel prior defogging algorithm is used to obtain the incident light component and reflected light component after defogging. Finally, a fog-free image was restored through the Reitnex model. The effectiveness of this algorithm is verified through experiments. By comparing and analyzing this algorithm with other defogging algorithms, this algorithm has higher contrast and color fidelity.
机译:为了提高空气图像的视觉效果,提出了一种暗通道前沿组合的视网膜缺失算法,解决了Reinex Defogging中的空中缺失性不足和过度增强现象。 首先,通过Retinex理论将有雾原始图像分解成有雾的入射光部件和有雾的反射光组件。 然后,通过大气散射模型分析有雾图像劣化原理,并且在缺少后,使用先前的Defogging算法的暗信道以获得入射光分量和反射光分量。 最后,通过Reitnex模型恢复了无雾图像。 通过实验验证了该算法的有效性。 通过将该算法与其他差错算法进行比较和分析,该算法具有更高的对比度和颜色保真度。

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