基于拉普拉斯滤波的形态相关器

Morphological Correlator Based on Laplace Filtering

本文提出了一种基于拉普拉斯滤波的形态相关器(LBMC),用来改进传统光学形态相关器的性能。与形态相关器不同,在执行最后的傅里叶变换之前,LBMC还须对传统形态相关器的联合功率谱做拉普拉斯能谱强度滤波处理。计算机模拟测试结果表明,与线性相关和形态相关器相比,LBMC能够产生强而尖锐的相关信号,具有更强的识别能力。当输入图像受椒盐噪声影响时,LBMC保持了高且稳定的自相关-互相关比和峰噪比,从而表现出更强的鲁棒性。尽管当乘法照明因子大于1时,LBMC丧失了传统MC的照明不变识别能力,但其保证相当高的识别度。

As a modified approach to improve the properties of the classical Morphological Correlation（MC）,a Laplace Filtering-based Morphological Correlator（LBMC） is proposed for pattern recognition.Different from classical MC,for the LBMC,the Joint Power Spectrum（JPS） summation of the MC is filtered by power spectrum of Laplace operator before final inverse Fourier transform.Computer simulation results show that,compared with the Linear Correlation（LC） and the conventional MC,LBMC provides better discrimination capability with sharp and strong unmistakable correlation signal,and its ACR（autocorrelation peak intensity to cross correlation peak intensity ratio） and Peak to Noise Ratio（PNR） are more stable when input scene is corrupted by outlier noise（salt-and-pepper noise）.Although the LBMC is not illumination invariant when multiplication illumination factor is larger than unity,considerable discrimination capability is still obtained.