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Improved image defogging method and its application in video monitoring system based on ARM

机译:改进的图像除雾方法及其在基于ARM的视频监控系统中的应用

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Purpose - The purpose of this paper is to improve an image defogging algorithm based on a dark channel prior and use this method to clear the foggy image on the Advanced RISC (Reduced Instruction Set Computing) Machines (ARM) platform. Design/methodology/approach - The divided strategy of the foggy image was proposed through the estimation of the brightness and transmission thresholds. The two regions of the foggy image were processed using two transmissions. Many foggy images were tested using the improved method. Findings - The finding resulting from this study is that a divided strategy has been proposed to use the image defogging. Compared with the existing methods, the running time of the improved method is less on the ARM platform. Practical implications - Image enhancement is an important technology of digital images, and the quality of images plays a key role in the video monitoring and the intelligent transportation system. Originality/value - This paper presented an improved image defogging method using the divided strategy and a substantial number of experimental results was provided to demonstrate this method.
机译:目的-本文的目的是改进一种基于暗通道先验的图像除雾算法,并使用此方法在Advanced RISC(精简指令集计算)机器(ARM)平台上清除模糊图像。设计/方法/方法-通过估计亮度和透射阈值,提出了模糊图像的划分策略。使用两个传输来处理雾图像的两个区域。使用改进的方法测试了许多模糊图像。结果-这项研究得出的结果是,提出了一种使用图像除雾的划分策略。与现有方法相比,改进方法在ARM平台上的运行时间更少。实际意义-图像增强是数字图像的重要技术,图像质量在视频监控和智能运输系统中起着关键作用。原创性/价值-本文提出了一种使用分割策略的改进图像除雾方法,并提供了大量实验结果来证明该方法。

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