Phase-only filtering based on sliced orthogonal nonlinear generalized decomposition

The sliced orthogonal nonlinear generalized (SONG) decomposition and correlation have been demonstrated to be powerful tools in digital image processing and promising for nonlinear optical information processing. In this paper, we propose an optical phase-only filtering system based on SONG decomposition (PBS), in which the phase-only filtering of the target and the input scene binary slices are performed separately by pairs and then added together. We numerically show that the PBS has extremely high and sharp output correlation peak compared with other optical correlators. Furthermore, such a SONG decomposition based phase-only filtering naturally inherits the nature of SONG decomposition, which has strong robustness to additive Gaussian noise and substitutive noise, and also the high light efficiency of phase-only filtering. We demonstrate that the PBS may serve as an optimized optical correlation scheme, which is promising in nonlinear optical pattern recognition.     

Composite wavelet based morphological correlation for continuous-scale-invariant pattern recognition

A composite nonlinear correlation is proposed to perform invariant recognition for the input image with continuous-scale distortions. The proposed correlation can be considered as a summation of many composite wavelet matched filters. Every matched filter consists of a linear combination of binary slices that are generated from threshold decomposition of the training images, and an adaptive wavelet filter. The adaptive wavelet is optimized to produce the sparse image features. Computer simulations are carried out to prove the scale-invariance and noise robustness of the new scheme.     

Shift- and scale-invariant pattern recognition using morphological fringe-adjusted joint transform correlation

A shift- and scale-invariant version of morphological fringe-adjusted joint transform correlation (MFJTC) is proposed in this paper, which we call shift- and scale-invariant MFJTC (SIMFJTC). SIMFJTC is combination of MFJTC and conventional radial harmonic filter (RHF). Using computer simulation, we compare the output results of SIMFJTC with those of morphological radial harmonic correlation (MRHC) and SDF-based FPFJTC when input scene is corrupted by salt-and-pepper noise and cluttered background. Our results show that SIMFJTC has higher discriminability and displays better stability against salt-and-pepper noise and cluttered background. Moreover, scale-invariance of SIMFJTC is much stricter than MRHC and SDF-based FPFJTC.     

Rotation-invariant pattern recognition using morphological fringe-adjusted joint transform correlation

We propose a rotation-invariant nonlinear correlator based on circular harmonic filter (CHF) and morphological Fringe-adjusted Joint Transform correlation (MFJTC). We refer to this correlator as a rotation-invariant MFJTC (RIMFJTC). Through computer simulation, we compare the output results of RIMFJTC with those of rotation-invariant MC (RIMC) and CHF when input scene is corrupted by salt-and-pepper noise, white additive Gaussian noise and cluttered background. Our results show that RIMFJTC yields higher discriminability, sharper and higher correlation peaks, and displays better stability against the above three kinds of noise than do the RIMC and common CHF.     

改进形态学相关算法以识别高相似度灰度图像

从形态学角度定义了灰度联合图像相似度，提出两种基于位表示法形态学相关算法的改进算法，通过提取位表示法的图像片边缘特征或二元化位表示法的图像片功率谱，以提高位表示法形态学相关算法对高相似度灰度图像的识别能力。     

Binary phase only filters for rotation and scale invariant pattern recognition with the joint transform correlator

The joint transform correlator (JTC) is one of the two main optical image processing architecture which provides a highly effective way of comparing images in a wide range of applications. Traditionally, an optical correlator is used to compare an unknown input scene with a pre-captured reference image library, to detect if the reference occurs within the input. Strength of the correlation signal decreases rapidly as the input object rotates or varies in scale relative to the reference object. The aim of this paper is to overcome the intolerance of the JTC to rotation and scale changes in the target image. Many JTC systems are constructed with the use of ferroelectric liquid crystal (FLC) spatial light modulators (SLMs) as they provide fast two-dimensional binary modulation of coherent light. Due to the binary nature of the FLC SLMs used in the JTC systems, any image addressed to the device need to have some form of thresholding. Carefully thresholding the grey scale input plane and the joint power spectrum (JPS) has significant effect on the quality of correlation peaks and zero order (DC) noise. A new thresholding technique to binarise the JPS has been developed and implemented optically. This algorithm selectively enhances the desirable fringes in the JPS which provide correlation peaks of higher intensity. Zero order noise is further reduced when compared to existing thresholding techniques.Keeping in mind the architecture of the JTC and limitations of FLC SLMs, a new technique to design rotation and scale invariant binary phase only filters for the JTC architecture is presented. Filers design with this technique have limited dynamic range, higher discriminability among target and non-target objects, and convenience for implementation on FLC SLMs. Simulation and experiments shows excellent results of various rotation and scale invariant filters designed with this technique. A rotation invariant filter is needed for various machine vision applications of the JTC. By fixing the distance between camera and input object, the scale sensitivity of the correlator can be avoided. In contrast to the industrial machine vision applications, scale factor is very important factor for the applications of the JTC systems in defence and security. A security system using a scale invariant JTC will be able to detect a target object well in advance and will provide more time to take a decision.     

Simulation and experiment research of face recognition with modified multi-method morphological correlation algorithm

Morphological definition of similarity degree of gray-scale image and general definition of morphological correlation (GMC) are proposed. Hardware and software design for a compact joint transform correlator are presented in order to implement GMC. Two kinds of modified general morphological correlation algorithm are proposed. The gray-scale image is decomposed into a set of binary image slices in certain decomposition method. In the first algorithm, the edge of each binary joint image slice is detected, width adjustability of which is investigated, and the joint power spectrum of the edge is summed. In the second algorithm, the joint power spectrum of each pair is binarized or thinned and then summed in one situation, and the summation of the joint power spectrums of these pairs is binarized or thinned in the other situation. Computer-simulation results and real face image recognition results indicate that the modified algorithm can improve the discrimination capabilities with respect to the gray-scale face images of high similarity.     

仅用参考物功率谱取阈的二元联合变换相关器

提出一种用特征物功率谱取阈值的新型二元联合变换相关器。与传统的联合变换相关器相比较,它有高光能效率、高鉴别率和输入空间宽带的优点;与现行的二元联合变换相关器相比较,它有鉴别率高和不需靶物功率谱测量的特点,因而是一种简便和高性能的相关器。     

Complementary-reference and complementary-scene for real-time fingerprint verification using joint transform correlator

In this paper, a new configuration for the input joint images in the joint transform correlator is proposed for fast real-time binary characters and fingerprints verification. In the proposed scheme, the input joint image has a complementary-reference image and a complementary target image in addition to the reference and the target images. We use the cross-correlation peak value between the reference and the complementary target image and the cross-correlation peak value between the complementary reference and the target images as the criteria to perform the recognition of the target in the input scene. It is shown that these two cross-correlation peak values will be zero if and only if the input target matches the reference image. One advantage of using the proposed scheme is the elimination of the usual and necessary time-consuming normalization of the input images in the general correlation-based matching processes. Another advantage of the proposed scheme is the insensitive to light-sources intensity fluctuations that usually limits the matched-based recognition approaches. The scheme is employed to verify binary characters and fingerprints images; further, it is employed to verify occluded fingerprints target images on one hand, and to determine if a specific part or pattern exists in the target fingerprint image on the other hand.     

多目标识别的联合变换相关器的研究

提出了一种可用于多目标识别的联合变换相关器。为改善相关信号的性能,对功率谱作了优化处理。为消除相关面上的零级项和目标间的相关项,可用联合功率谱减去纯目标输入的功率谱和参考图像的功率谱;为增强和锐化相关峰,将相减的功率谱作指数函数滤波处理。分析了指数滤波参数对相关结果的影响。计算机模拟结果表明,这种相关器所输出的相关信号比经典联合变换相关器和二元联合变换相关器输出的相关信号更好,互相关得到了抑制,自相关得到了增强,具有很好的抗噪能力。     

Enhanced Optical Image Verification Based on Joint Transform Correlator Adopting Fourier Hologram

In this paper two new architectures for optical image verification are proposed. Both architectures are based on conventional joint transform correlators (JTCs) adopting a Fourier hologram and can significantly improve the recovered image quality. First, an input phase-only function is Fourier transformed and then interferes with a reference wave that is diffracted from a plane wave incident on another random phase mask. Second, two phase-only functions are placed at the two input sides of a beamsplitter such that the interference pattern of their Fourier transforms can be detected. To obtain a predefined target image in the output plane, one of the input phase functions is iteratively retrieved by the use of the projection onto constraint sets algorithm. Simulation results show that the less mean squared error and better image quality are obtained for both the binary and grayscale images.     

Binary neutron stars gravitational wave detection based on wavelet packet analysis and convolutional neural networks

This work investigates the detection of binary neutron stars gravitational wave based on convolutional neural network(CNN).To promote the detection performance and efficiency,we proposed a scheme based on wavelet packet(WP)decomposition and CNN.The WP decomposition is a time-frequency method and can enhance the discriminant features between gravitational wave signal and noise before detection.The CNN conducts the gravitational wave detection by learning a function mapping relation from the data under being processed to the space of detection results.This function-mapping-relation style detection scheme can detection efficiency significantly.In this work,instrument effects are con-sidered,and the noise are computed from a power spectral density(PSD)equivalent to the Advanced LIGO design sensitivity.The quantitative evaluations and comparisons with the state-of-art method matched filtering show the excellent performances for BNS gravitational wave detection.On efficiency,the current experiments show that this WP-CNN-based scheme is more than 960 times faster than the matched filtering.     

使用振幅调制和功率谱相减的联合变换相关器作多目标检测

提出一种使用振幅调制和功率谱相减的联合变换相关器作多目标检测，这一方法对联合功率谱作了修正，先将联合功率谱减去纯输入景物的功率谱和参考图象的功率谱，再将所得修正的联合功率谱乘以振幅调制滤波函数。分析和量化了输入景物噪声对联合变换相关器性能的影响。这种方法比条纹调节的联合变换相关器和修正的条纹调节的联合变换相关器能产生更好的相关输出和适应输入景物噪声的能力。     

高通滤波的二元联合变换相关器

提出一种新的采用高通滤波的二元联合变换相关器，这种相关器与一般的二元联合变换相关器的差别在于联合功率谱作二元处理之前先进高通滤波，使用这种技术，可以产生比二元联合变换相关器更好地相关输出性能，给出对含有灰度级场体的输入景物的计算机模拟结果。     

Joint transform correlator based on off-focus inputting and spherical wave illuminating power spectrum

An improved joint transform correlation technique is proposed for efficient multiple-target detection. The proposed technique employs off-focus inputting and spherical wave illuminating joint power spectrum to overcome false-target detection by eliminating the false correlation peaks while alleviating the effects of noise and other artifacts. Compared with the reported techniques, the proposed method does not need preprocessing for reference image and Fourier plane phase filtering, which makes the recognition process more suitable for all-optical setup to be realized. Thus the speed advantage of the recognition system is more prominent. Moreover, the proposed technique can maximize the utilization efficiency of the space-bandwidth product and the CCD by the new input method. The feasibility and effectiveness of the proposed method are demonstrated by numerical results.     

使用参考光波光学联合变换相关加密系统的选择明文攻击

证实了一种使用参考光波的光学联合相关变换加密系统对于选择明文攻击的脆弱性。在该加密系统中,通过选择一个透过率为零的特殊明文图像,记录其对应的联合功率谱,之后再通过遮挡输入面获取参考光波强度、遮挡参考光和明文获得加密密钥的傅里叶变换强度,根据获得的3幅图像,攻击者可以准确地获取加密所用的密钥,进而可以恢复出原始图像。理论分析和计算机模拟结果均证明所提攻击方法的有效性。     

用于指纹识别的基于离散余弦变换的二值化联合变换相关器

提出了一种利用离散斜弦变换对联合功率谱进行处理的二值化联合变换相关算法,利用这种二值联合变换相关器,进行了一个待识别指纹同四个参考指纹的比较,这种相关器同采用局部中值阈值技术的二值化联合变换相关器相比,能提高输出峰边比,提高相关峰的强度。光电混合处理实验的结果表明,这种方法能大大提高多指纹识别系统的识别性能。     

实时高效联合变换相关器

提出一种利用光学波分复用器实现实时高效联合变换相关的方案。通过计算机控制把输入面分为多个大小相等的窗口，分别写入参考与目标图像，利用光学波分复用器于相关系统中，使对应不同窗口的读出光学信息在第一个焦面上形成联合功率谱阵列，在输出面上可以实时地获得增强了相关信号。     

Embedding color watermarks in color images based on Schur decomposition

In this paper, a blind dual color image watermarking scheme based on Schur decomposition is introduced. This is the first time to use Schur decomposition to embed color image watermark in color host image, which is different from using the binary image as watermark. By analyzing the 4 × 4 unitary matrix U via Schur decomposition, we can find that there is a strong correlation between the second row first column element and the third row first column element. This property can be explored for embedding watermark and extracting watermark in the blind manner. Since Schur decomposition is an intermediate step in SVD decomposition, the proposed method requires less number of computations. Experimental results show that the proposed scheme is robust against most common attacks including JPEG lossy compression, JPEG 2000 compression, low-pass filtering, cropping, noise addition, blurring, rotation, scaling and sharpening et al. Moreover, the proposed algorithm outperforms the closely related SVD-based algorithm and the spatial-domain algorithm.     

Extended fractional wavelet joint transform correlator

An extended fractional wavelet joint transform correlator is implemented for real-time target recognition applications. The real-time input scene captured using a charge-coupled device camera along with the reference image is fractional Fourier transformed. The obtained joint power spectrum is multiplied by an appropriately scaled wavelet filter and the resultant function is differentiated. The application of wavelet filter enhances the correlation outputs and differential processing of wavelet-filtered joint power spectrum improves the detection efficiency by reducing the zero-order spectra. Targets with Gaussian and speckle noise have also been used to check the correlation output. The performance metrics: correlation peak intensity, peak-to-correlation energy, peak-to-sidelobe ratio and signal to clutter ratio have been calculated. The experimental results are presented in support of the proposed idea.