随着雾霾等恶劣天气的日益加强及战场烟尘环境对**作战的影响,在烟雾环境下对目标的辨认、探测与识别受到了广泛的关注。基于此,提出多小波融合的偏振探测去雾技术,该技术以目标偏振探测为基础,应用多小波的对称性、正交性和紧支集性等优点,根据分解后高、低频系数所具有的特点分别采用不同的规则对目标偏振信息进行融合。相比于传统小波融合,该算法更易突显目标轮廓及反映目标的细节信息。利用该技术对实际烟雾环境下的目标进行大量外场探测实验,分别对图像的主观评价和客观评价标准进行验证,结果表明该技术在主观视觉效果及对比度、清晰度、空间频率等客观评价方面都具有显著优势,提高了雾天环境下目标的识别效率。

With the recently increasing influence of haze/fog and other inclement weathers and the expanding impact of smoke and dust in the battlefield on military operations, the identification, detection and recognition of targets in smoke and fog environment draw much more attentions. Thus based on this point, the polarization detection defogging technology based on multi-wavelet fusion is proposed. This technology is built on the target polarization detection and simultaneously combined with the merits of multi-wavelet, such as symmetry, orthogonality and compact support. According to the features of the high and low frequency coefficients, the different fusion rules are adopted for the fusion of target polarization information. This algorithm is much easier to get the prominent target contour and detail information than the traditional wavelet fusion. A large number of outfield target detection experiments are applied in the actual fog and haze environment. Both the subjective and objective evaluation criteria show that this technology has obvious advantages in the subjective visual effect and the objective evaluation aspects of contrast, definition, spatial frequency and so on, which can increase the identification efficiency of targets in fog environment.