Liu Bohan, Wei Qihai, Ding Kun
Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2024 Apr 3;24(7):2276. doi: 10.3390/s24072276.
Under a foggy environment, the air contains a large number of suspended particles, which lead to the loss of image information and decline of contrast collected by the vision system. This makes subsequent processing and analysis difficult. At the same time, the current stage of the defogging system has problems such as high hardware cost and poor real-time processing. In this article, an image defogging system is designed based on the ZYNQ platform. First of all, on the basis of the traditional dark-channel defogging algorithm, an algorithm for segmenting the sky is proposed, and in this way, the image distortion caused by the sky region is avoided, and the atmospheric light value and transmittance are estimated more accurately. Then color balancing is performed after image defogging to improve the quality of the final output image. The parallel computing advantage and logic resources of the PL (Programmable Logic) part (FPGA) of ZYNQ are fully utilized through instruction constraints and logic optimization. Finally, the visible light detector is used as the input to build a real-time video processing experiment platform. The experimental results show that the system has a good defogging effect and meet the real-time requirements.
在雾天环境下，空气中含有大量悬浮颗粒，这会导致图像信息丢失以及视觉系统采集的对比度下降。这使得后续的处理和分析变得困难。同时，现阶段的去雾系统存在硬件成本高和实时处理性能差等问题。本文设计了一种基于ZYNQ平台的图像去雾系统。首先，在传统暗通道去雾算法的基础上，提出了一种天空分割算法，通过这种方式，避免了天空区域引起的图像失真，并且更准确地估计了大气光值和透射率。然后在图像去雾后进行颜色平衡，以提高最终输出图像的质量。通过指令约束和逻辑优化，充分利用了ZYNQ的PL（可编程逻辑）部分（FPGA）的并行计算优势和逻辑资源。最后，以可见光探测器作为输入构建了一个实时视频处理实验平台。实验结果表明，该系统具有良好的去雾效果并满足实时要求。
