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Methods of Restoring a Weather Degradation Image Based on Physical Model and Their Application

机译:基于物理模型的天气退化图像恢复方法及其应用

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The contrast and color of a weather degradation image are bad. Lacking of some parameters, it's difficult to restore the contrast and color of the scene under the fine weather by only one weather degradation image. In this paper two simple methods of restoring a weather degradation image, depth developmental method and depth estimate method, are introduced. The two methods bases on the dichromatic armospheric scattering model. It can delete the effect of weather in an image, without any additional weather and depth information. It only needs an image in bad weather and simple information provide interactively by the user. The intensity of the restored image degrades. So we use the histogram intensity adjusting method and depth intensity adjusting method respectively to enhance and adjust the intensity of the image. We simulate the two methods in Matlab, and compare between them. Simulation results show that the effect of the two methods in restoring a weather degradation image is good.
机译:天气退化图像的对比度和颜色差。缺少某些参数,仅凭一张天气退化图像就很难在晴朗的天气下恢复场景的对比度和色彩。本文介绍了两种还原天气退化图像的简单方法,深度开发方法和深度估计方法。两种方法都基于双色的大气层散射模型。它可以删除图像中天气的影响,而无需任何其他天气和深度信息。它只需要恶劣天气下的图像,并且用户可以交互地提供简单的信息。恢复的图像的强度降低。因此,我们分别使用直方图强度调整方法和深度强度调整方法来增强和调整图像的强度。我们在Matlab中模拟了这两种方法,并进行了比较。仿真结果表明,两种方法在恢复天气退化图像方面效果良好。

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