基于GL-MSR的火灾监控图像去雾研究

针对建筑物中发生火灾时，内部闭路电视系统在热烟气影响下监控图像效果差的问题，提出一种融合高斯金字塔和对数查表法的多尺度 Retinex（GL-MSR）火灾监控图像去雾方法。构建基于 GL-MSR 的火灾图像增强模型，并利用高斯金字塔和对数查表法减少图像处理时间。实验结果表明：基于 GL-MSR 的图像处理时间是传统 MSR 方法的 1/26；在应急照明灯情况下烟雾图像处理效果比红外线照明情况下更佳；与传统的去雾算法相比，GL-MSR 处理后的烟雾图像更为清晰，能够有效提高火灾现场监控图像的监控效果。

Research on defogging of fire monitoringimage based on GL-MSR

In the event of a fire in a building, the internal CCTV system has poor monitoring images under the influence of hot smoke. A multi - scale Retinex (GL - MSR) fire defogging method combining Gaussian pyramid and log lookup table is proposed to improve the monitoring effect in complex fire situations. A fire image enhancement model based on GL - MSR was constructed, and the Gaussian pyramid and log lookup table method were used to reduce the image processing time. The experimental results show that the image processing time based on GL - MSR is 1/26 of the traditional MSR method. The smoke image processing effect is better in case of emergency lighting than infrared lighting. In comparison, the processed smoke image of GL - MSR is clearer, which can effectively improve the monitoring effect of the fire scene monitoring image.