With the rapid advancement of video and image processing technologies in the Internet of Things, it is urgent to address the issues in real-time performance, clarity, and reliability of image recognition technology for a monitoring system in foggy weather conditions. In this work, a fast defogging image recognition algorithm is proposed based on bilateral hybrid filtering. First, the mathematical model based on bilateral hybrid filtering is established. The dark channel is used for filtering and denoising the defogging image. Next, a bilateral hybrid filtering method is proposed by using a combination of guided filtering and median filtering, as it can effectively improve the robustness and transmittance of defogging images. On this basis, the proposed algorithm dramatically decreases the computation complexity of defogging image recognition and reduces the image execution time. Experimental results show that the defogging effect and speed are promising, with the image recognition rate reaching to 98.8% after defogging.

中文翻译：

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一种基于双边混合滤波的快速去雾图像识别算法

随着物联网视频和图像处理技术的飞速发展，迫切需要解决多雾天气条件下监控系统图像识别技术的实时性、清晰度和可靠性等问题。在这项工作中，提出了一种基于双边混合滤波的快速去雾图像识别算法。首先，建立了基于双边混合滤波的数学模型。暗通道用于对去雾图像进行滤波和去噪。其次，提出了一种结合引导滤波和中值滤波的双边混合滤波方法，可以有效提高去雾图像的鲁棒性和透射率。在此基础上，该算法显着降低了去雾图像识别的计算复杂度，减少了图像执行时间。实验结果表明，去雾效果和速度都很好，去雾后的图像识别率达到了98.8%。