用于模式识别的一种新的光学相关器

我们研究了一种新的白光联合变换相关器，即在频谱面上利用液晶光阀对联合傅氏干涉谱进行变换，然后用白光做为液晶光阀的读出光，实现相关变换。利用部份相干光传播模式，导出这种白光联合相关器保留了对复振幅的线性运算能力，结果表明，这种相关器能得到较好的相关结果，并能有效地抑制相干噪声。     

用功率谱复制技术实现高效联合变换相关

提出利用复制技术对高通滤波后的功率谱复制多份以获得高效的联合变换相关。平方律探测器CCD将功率谱输入计算机,经相减运算和Butter-worth高通滤波后,将其复制成N份,戍阵列形式呈现在空间光调制器上,经光学傅里叶变换得到信号相叠加的高效相关输出。计算机模拟和光学实验结果表明,这种高效相关器能够抑制相关面上的中央零级项,增强、锐化一级相关峰,信噪比提高了4倍多,N份功率谱阵列对应的输出峰值强度约是单份功率谱对应强度的N倍。     

抗噪性联合变换相关器

我们对联合变换相关器的输入图象进行Roberts梯度处理,同时对参考图象采取相移技术,并在频域中将功率谱二值化。与传统的联合变换相关器（CJTC）相比,新型的联合变换相关器（NJTC）消除了功率谱的直流分量,锐化了相关峰强度,提高了衍射效率和识别能力,同时增强了联合变换相关器的抗噪性能。用计算机模拟出预言结果。     

实时联合变换相关器目标探测与识别

光学自动图像识别的基本结构是光学相关器,由于光学相关是所有采样点并行处理,运算速度高于计算机千百倍.本文用电寻址液晶EALCD作为空间光调制器SLM,用计算机控制的EALCD并排显示参考信号和实时扫描的目标信号,并用面阵CCD作为平方律探测器记录其联合变换功率谱,通过光学傅立叶变换,输出相关信号,识别目标并确定目标在空间的方位.其特点是,由于用CCD探测功率谱,可以用各种数字处理技术提高系统的信噪比,并能更精确的探测和识别目标.     

基于SONG相关的相位编码联合变换相关识别

为了提高光学联合变换相关识别的综合性能,提出一种基于SONG相关的参考图像相移相位编码条纹调制畸变不变联合变换相关器.该相关器引入SONG相关技术和SDF方法,具有更加突出的抑制干扰信号能力、抗噪声性能和多目标识别能力,通过修正SDF的约束条件,当输入图像存在多个畸变目标时,能够较好地实现相关输出的畸变不变性.仿真实验结果表明:当输入图像受到非覆盖性背景噪声影响时,该相关器在整个测试噪声强度区间内输出相关峰强度和峰噪比分别是引入SONG相关技术前的1.87～5.16倍和1.88～5.19倍,其平均偏差量能够基本维持在0.04以下;当输入图像受到替换噪声影响时,该相关器在大部分测试噪声强度区间内都能给出较高的相关峰强度和峰噪比,在噪声强度不高于0.4时,其平均偏差量能够低于0.1.     

利用液晶光阀实现的Joint变换

本文叙述了Joint变换的基本原理,并利用液晶光阀的偏振调制特性实现了Joint变换,液晶光阀作为实时记录器件,可以对物体的频谱进行改善,从而得到了较好的相关输出,实验结果与理论分析相符,提供了实时光学相关的一种新方法。     

二元联合变换相关器的实现方法研究

采用中值取阈，局部取阈，参考图像功率谱取阈和联合功率谱（JPS）取阈四种方法对传统联合变换相关器的功率谱二值化，从而将振幅调制的功率谱转化为脉冲调制的功率谱。计算机模拟结果表明二值化可以获得更清晰更尖锐的相关峰，其中联合功率谱取阈法的识别效果最佳。     

基于拉普拉斯滤波的形态相关器

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.     

折叠式集成化光学相关器

利用超短光路结构和空间折叠光路结构,研制出一种小型多功能光学相关器,它能高速处理256×256像素图像。光学相关器易上下拆卸,并方便地实现Vander Lugt相关和联合变换相关之间的互换。实验结果证实了该系统具有较好的相关性能。     

基于JTC和扩频技术的多二值图像光学加密技术

为了提高光学加密系统的传输效率和安全性,提出了一种多二值图像光学加密技术。该方法加密时采用数字方法和光学方法联合实现,解密过程可采用纯光学方法实现。加密时,首先将待加密图像乘以不同密钥进行频谱扩展,再进行算术叠加生成复合图像。然后将复合图像置于联合变换相关器的输入面上进行光学加密。解密时,需要在频率域利用光阑从复合图像中提取出每一幅原始图像。理论分析和计算机仿真表明,该多二值图像光学加密技术系统结构简单,图像复用容量巨大,具有较高的安全性。     

Dual nonlinear correlator based on computer controlled joint transform processor: Digital analysis and optical results

Abstract

The hybrid optoelectronic processor, presented in this paper, realizes the dual nonlinear correlation (DNC) in a set-up based on a two-step nonlinear joint transform correlator architecture. In the first step three power spectrum distributions (input scene power spectrum, reference target power spectrum, and the joint power spectrum) necessary for the nonlinear processing are captured with a CCD camera. Nonlinear modification of the joint power spectrum, which does not have to be symmetrical in the input and reference channels, is introduced digitally. In the second step, the modified joint power spectrum is Fourier transformed optically. Numerical analysis of this processor shows a crucial influence of the dynamic range and the limited number of grey levels of the CCD camera during image acquisition in the first step, on the output signal parameters and the discrimination capability of the set-up. Optical results of recognition obtained for noise-free segmented input scenes show that the set-up enables the realization of various correlation operations as CMF, POF, IF, PPC, etc. without any filters and that the discrimination capability is easy to control by a proper selection of the type of nonlinear processing.     

Modified fringe-adjusted joint transform correlation to accommodate noise in the input scene

A modified fringe-adjusted joint transform correlator is proposed that is able to accommodate noise in the input scene. The effect of noise in the input scene on the performance of the joint transform correlator is analyzed and quantified. When the target is embeddedin aseverely noise-corrupted input scene, it is shown that the proposed modified fringe-adjusted filter joint transform correlator delivers a better correlation performance and the capacity to accommodate this noise than does the fringe-adjusted filter-based correlator. When the power spectra of the input image and the reference image are subtracted from the power spectrum of the joint-input image, it is found that the noise effect on the output plane is independent of the objects in the input scene and originates from the convolution of the reference image and noise in the input scene.     

Multiple-target detection with use of a modified amplitude-modulated joint transform correlator

Multiple-target detection with a modified amplitude-modulated joint transform correlator is proposed. With this technique the joint power spectrum is first modified by the subtraction of the power spectrum of the input scene only and of the reference image from it; the resultant modified joint power spectrum is next multiplied by the amplitude-modulated filter function. The effect of noise in the input scene on the performance of the joint transform correlator is analyzed and quantified. This technique is found to deliver a correlation output and the capacity to accommodate noise in the input scene better than both the fringe-adjusted filter-based joint transform correlator and the modified fringe-adjusted filter-based joint transform correlator.     

联合变换图像识别中功率谱高斯掩膜处理方法

本文提出了一种基于在光学频谱面上进行光学高斯高通滤波的实时处理方法.此方法将一个高斯掩膜覆盖在位于光学频谱面上的CCD中心位置,从而明显降低了相关图像中自相关峰的高度和宽度.通过比较不同的参数效果,确定了一种用于实验的高斯函数滤波器.通过系列实验研究发现,本方法可以明显提高联合变换相关器的效果和速度.     

Image classification with a chirp-encoded joint transform correlator

We describe a method of performing image classification with a chirp-encoded joint transform correlator. In the proposed system the reference images and the input image that is to be classified are placed in different input planes of the joint transform correlator. As a result, different output planes of the correlator are associated with each reference image. The input image is classified on the basis of the intensity and the spatial position of the correlation peak. The reference images and the input image can be positioned in one input plane with glass blocks of different thicknesses placed on each reference image. This produces the same effect as having the reference images and the input image in different planes. Analytical expressions, computer simulations, and optical experiments are presented to investigate the performance of the chirp-encoded joint transform correlator for image classification.     

Complementary-reference joint transform correlator

We present a new input configuration for the joint transform correlator called a complementary-reference joint transform correlator (CRJTC). The difference between the CRJTC and the existingjoint transform correlator is that the CRJTC has an additional complementary reference in the input plane. We use a criterion defined as the ratio of the cross correlation between the target and the reference to the cross correlation between the target and the complementary reference to perform recognition. This ratio can attain its maximum if and only if the reference and the target are matched and if it is stable to the light-source intensity fluctuations; therefore it is unnecessary to normalize the input images. The CRJTC is suitable for the recognition of a binary-amplitude image only. The experimental demonstration of a CRJTC is given.     

Binary joint transform correlator based on differential processing of the joint transform power spectrum

A novel binary joint transform correlator with differential processing in the joint transform power spectrum is proposed. The new model of the binary joint transform correlator can eliminate the dc component and sharpen the correlation intensity peaks, hence increasing its discrimination ability but with a lower complexity of computation. Preliminary results are shown by computer simulations.     

Feature-extracted joint transform correlation

A new technique for real-time optical character recognition that uses a joint transform correlator is proposed. This technique employs feature-extracted patterns for the reference image to detect a wide range of characters in one step. The proposed technique significantly enhances the processing speed when compared with the presently available joint transform correlator architectures and shows feasibility for multichannel joint transform correlation.