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Artificial Haze Immune Algorithm for Image Processing

机译:人工雾霾免疫算法的图像处理

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摘要

The Intelligent Transportation Systems bring a safely and comfortable motorized society, which are based on image processing such as predicting/detecting the danger of vehicles collecting the transport information to control the traffic flow on traffic control systems etc. However, with the pollution of environment, the fog/haze becomes a serious problem, causing the image deterioration or degradation and the Intelligent Transportation Systems lose their functions. This paper proposed an immunological method of image processing for detecting the fog/haze in the image to support Intelligent Transportation Systems. This state-of-the-art method is based on the theory of biological defence system, which unites the reducing of fog/haze and edge detection. The experimental results show that our proposed haze immunized algorithm can remove effect of haze on image processing algorithm. Compared to conventional de-haze image processing algorithm, our proposed algorithm unitizes bio-inspired algorithm to achieve efficient hardware consumption. The results of FPGA implementation show less hardware usage than conventional method.
机译:智能交通系统基于图像处理(例如,预测/检测车辆收集交通信息的危险以控制交通控制系统上的交通流等)而带来的安全舒适的机动化社会。但是,随着环境的污染,雾/雾成为一个严重的问题,导致图像质量下降或退化,并且智能交通系统失去功能。提出了一种图像处理的免疫学方法,用于检测图像中的雾霾,以支持智能交通系统。这种最先进的方法基于生物防御系统的理论,该理论将减少雾霾和边缘检测结合在一起。实验结果表明,本文提出的雾霾免疫算法可以消除雾霾对图像处理算法的影响。与传统的除雾图像处理算法相比,我们提出的算法结合了生物启发算法以实现高效的硬件消耗。 FPGA实现的结果显示,与传统方法相比,硬件使用量更少。

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