改进的雾霾天气交通标志图像去雾算法

现有去雾算法直接应用于交通图像时容易出现过渡区域明显、偏色严重，不能满足后续交通标志检测系统的应用要求，为此提出一种改进的基于暗原色先验的单幅交通图像去雾算法。首先利用改进的均值漂移算法对交通图像进行天空区域分割，并对分割后的天空区域采用直方图均值化算法去雾，对非天空区域使用基于快速双边滤波的暗原色先验算法去雾，最后通过图像融合得到最终去雾图像。实验结果表明，相比其他几种典型去雾算法，所提算法对交通标志图像天空区域的过渡区域和色彩失真现象有所改善，且具有较快的处理速度，通过定量分析可知去雾效果较好，能够满足后续交通标志检测系统的应用要求。

Modified image dehazing algorithm of traffic sign image in fog and haze weather

When directly applying the existing fog algorithms to the traffic image, the transitional region is obvious and the color cast is serious, which can not meet the requirement of subsequent traffic sign detection. In order to solve this problem, a modified single traffic image dehazing algorithm based on dark channel prior image was proposed. Firstly, the modified mean shift algorithm was used to segment the sky region of traffic image; then the histogram equalization algorithm was used to defog the partitioned sky region, and the dark channel prior algorithm based on efficient bilateral filter was used to defog the non-sky region. At last, the final image dehazing was finished by image fusion. Experimental result shows that compared with the typical image dehazing algorithms, the proposed algorithm has better effect in transitional region of the sky, the color cast is not serious, and its processing speed is faster; the quantitative analysis result indicates that the proposed algorithm has better effect in dehazing, and can meet the requirement of subsequent traffic sign dectection system.