FPGA Design of Image Defogging System in Intelligent Tachograph

Abstract

In hazy weather, due to the low visibility of traffic roads, the video images collected are degraded and the image information is fuzzy. Considering the problem of low real-time processing of the traditional system, an image defogging system based on the ZYNQ platform is designed and applied to the intelligent driving recorder system. First, aiming at the problems of the traditional dark channel defogging algorithm in the sky region, a sky region segmentation strategy is proposed to correct the image restoration parameters. Then, in order to solve the problem that the pixel ordering of the whole image consumes a lot of resources when calculating the global atmospheric light value, a frame iteration method is proposed to optimize the atmospheric light value by making the advantage of the parallel operation on the FPGA platform, and at the same time, the optimization of guided filtering is realized. Finally, using dual-channel high definition multimedia interface (HDMI) resources, a real-time traffic image video processing experimental platform is established by using one channel of the dual HDMI resources as video input and the other as video processing output, and experimental simulation of the algorithm in this paper is conducted. The experimental results show that the system has a good defogging performance for the traffic video in hazy weather, especially in solving the problem of defogging distortion in the sky area. When the traffic video with a resolution of 1 280×720 is defogged, the processing speed can reach 30 frame/s meeting the real-time requirements.

Keywords

• traffic video
• image defogging
• zynq platform
• real-time processing