摘要： 潜指纹紫外偏振图像由紫外强度图像与偏振度参量图像融合而成，可实现潜指纹准确检测与识别，然而目前无法选择最优偏振参量表征目标特性。在现有偏振图像融合算法基础上，提出一种紫外偏振图像模糊自适应融合算法。从紫外偏振图像解析出多个偏振参量图像，使用模糊积分自适应选择最佳偏振参量图像，利用离散平稳小波变换将紫外强度图像和最佳偏振参量图像分解为高、低频系数，按照最大值规则融合高频系数，采用稀疏表示规则融合低频系数，并通过离散平稳小波逆变换获得融合图像。实验结果表明，与LP、PCA等融合算法相比，该算法所得融合图像能更好地保留强度图像特征与偏振参量高频信息，提高目标对比度并增强目标细节特征，对不同材质的潜指纹适应性较强。

关键词: 紫外偏振, 偏振图像, 偏振参量, 自适应融合, 潜指纹

Abstract: The ultraviolet polarization image of latent fingerprint is fused of ultraviolet intensity image and polarization parameter image,which can realize accurate detection and recognition of latent fingerprint.However,it is impossible to select the optimal polarization parameter to represent the target characteristics.Based on the existing fusion algorithms for the polarization image,this paper proposes a fuzzy adaptive fusion algorithm for the ultraviolet polarization image.It analyzes multiple polarization parameter images extracted from the ultraviolet polarization image,and uses fuzzy integral to select the optimal polarization parameter image adaptively.Then the ultraviolet intensity image and the optimal polarization parameter image are decomposed into high and low frequency coefficients by using discrete Stationary Wavelet Transform(SWT).Also,the high frequency coefficients are fused based on the maximum rule,and the low frequency coefficients are fused based on the sparse representation rules.On this basis,the inverse discrete SWT is used to obtain the fused image.Experimental results show that compared with LP,PCA and other fusion algorithms,the proposed algorithm can better retain the features of intensity images and high frequency information of polarization parameters in the fused images.It improves the target contrast and enhances the target detail features,and has strong adaptability to different materials of latent fingerprints.

Key words: ultraviolet polarization, polarization image, polarization parameter, adaptive fusion, latent fingerprint

中图分类号: 

• TP391