李从利,薛松,陆文骏,张思雨(解放军陆军军官学院三系, 合肥 230031;解放军陆军军官学院研究生管理大队一队, 合肥 230031)
目的 偏振成像产生的偏振参量图像具有一定的揭示雾天目标相关特性的优势，目前尚无适当的量化评估手段，由于偏振参量图像均由原方向图解析产生，针对解析类图像的质量评价问题利用现有方法无法有效解决，为此，提出一种用于雾天条件下偏振成像质量评价的方法，旨在给出不同雾天条件下偏振参量图像质量及其变化对比情况。方法 从图像质量分析角度验证雾天目标特性表征与主观观测一致性关系。在分析全偏振参量解析过程及雾天对图像质量的影响基础上，提取了与“解析失真”敏感的特征因子：基于空域的自然场景统计特征和图像的结构性特征，同时引入相应Stokes参量形成了偏振解析参量特征，依据马氏距离构建了统一的评价模型。结果 分别选取室内模拟雾天环境成像样本、仿真生成的雾天样本、室外实拍雾天成像样本3类样本。采用3个参数：1）非线性回归后的算法测试分数与DMOS（平均主观评份差值）间的线性相关系数（CC）；2）非线性回归后的算法测试分数与DMOS间；的均方根误差（RMSE）3）斯皮尔曼相关系数（SROCC）。开展了有效性实验及主客观一致性实验。采用本文算法评价的入射光强（I）图CC值和RMS值分别为0.930 2和4.593 2，偏振度（P）图的CC值和RMS值分别为0.877 1和0.995 0，算法准确度高。入射光强（I）图的SROCC值为0.939 0，P图的SROCC值为0.786 1，算法的客观分数与主观分数相一致。算法对不同雾天条件下的偏振解析参量图像的质量演变关系辨识性好，客观评价结果符合主观理论分析。结论 本文针对偏振参量图像提出的综合质量评价模型通过提取特征因子及Stokes参量形成的评价算法能够准确地评价参量图像中的I图和P图，算法准确度高、主客观一致性好，能够反映偏振参量图像的质量及相关关系，较好地解决了雾天条件下偏振成像质量评价问题。
Quality assessment of polarization imaging under foggy
Li Congli,Xue Song,Lu Wenjun,Zhang Siyu(3rd Department in Army Office Academy, Hefei 230031, China;1st Company of Administrant of Postgraduate in Army Office Academy, Hefei 230031, China)
Objective Images that are produced by polarization imaging have certain characteristics that reveal the advantages of fog goal. An effective quantitative evaluation method, however, has yet to be developed for polarization images. Given that the parameters of polarization images are generated by the original pattern, existing methods cannot effectively evaluate analytical images. The current study presents an evaluation method for the quality of polarization images under foggy conditions, as well as aims to compare the quality of images under different fog conditions.Methods The relationship between the characteristics and the subjective observation of fog was verified from the view of image quality analysis. A polarization analysis of the characteristic parameters and factors of "analytical distortion sensitive" was conducted by analyzing the process of all polarization parameters and the influence of fog on image quality. These factors were based on the structural characteristics of the spatial statistical characteristics of natural scenes and images. Then, the corresponding Stokes parameters were introduced. A unified evaluation model was developed based on Mahalanobis distance. The experiment analyzed indoor simulated fog scene samples, simulated fog samples, and images under actual conditions. Experiments and the indoor simulation of a foggy environment were conducted with samples. Samples under foggy conditions were analyzed and evaluated.Results The validity and consistency of the subjective and objective experiments were determined with the three types of samples. The experimental results show that the CC values and RMS values of the I map evaluated by the proposed algorithm are 0.930 2 and 4.593 2, respectively, and the CC value and RMS value of the P map are respectively 0.877 1 and 0.995 0, algorithm has high accuracy. The SROCC value of I is 0.939 0, the SROCC value of P is 0.786 1, the objective score of the algorithm is consistent with the subjective score. The algorithm is better for the identification of the quality evolution relation of the polarization resolution parameter images under different fog conditions, The objective evaluation results are in accordance with the subjective analysis.Conclusion In this paper, a comprehensive quality evaluation model based on polarization parameter image is proposed, which can accurately evaluate the I and P images in the parametric image by extracting the characteristic parameters and the Stokes parameters. The algorithm has high accuracy and good subjective and objective consistency, which can reflect the quality and correlation of the polarization parameter image, and can solve the problem of polarization imaging quality evaluation under the condition of fog.