Reduction in correlation-filter sensitivity to background clutter by the automatic spatial frequency selection algorithm

We propose an automatic spatial frequency selection correlation filter that reduces the sensitivity to nonoverlapping noise or background clutter. This is achieved by inclusion of distorted versions of the reference images surrounded by nonoverlapping background clutter. Furthermore, we impose that the window functions of the reference images give response zero-correlation amplitudes. Simulation results are provided in the case of a two-class pattern-recognition problem and show that the results are appreciably increased. The results are compared with a normal automatic spatial frequency selection.     

Optical correlation of spatial-frequency-shifted images in a photorefractive BSO correlator

The optical cross correlation of an image with another image that was spatial-frequency shifted in one dimension was demonstrated in a photorefractive VanderLugt correlator. The first image was stored as a Fourier-transform hologram in a photorefractive Bi12SiO20 crystal (BSO) and was successively correlated with different spatial-frequency-shifted versions of a second image. We implemented the spatial-frequency shift by rotating a galvanometer mirror in an image plane, causing the Fourier transform to be shifted laterally in the BSO. We verified that the resulting operation in the BSO was an accurate complex multiplication of the shifted and the stored Fourier transforms. As many as 20 successive readouts were conducted without measurable erasure of the stored hologram. The dynamic range, saturation behavior, and other performance parameters were measured and are discussed.     

Hybrid digital-optical correlation employing a chirp-encoded simulated-annealing-based rotation-invariant and distortion-tolerant filter

The simulated annealing (SA) algorithm based on entropy optimization is a technique of synthesizing distortion-invariant matched filters capable of discriminating very similar images. The synthesis of rotation-invariant filters using modified SA-based filter equations and their tolerance to distortions are studied. The filters are trained with true class images rotated in-plane at 3 degrees intervals between 0 degrees and 360 degrees . A total of seven filters are required over the whole range for both CCD or thermal images. Optical correlation in a hybrid digital-optical correlator results in an unwanted zero-order dc along with two first-order (+/-1) correlation peaks. A chirp function multiplied with the filter separates out the three peaks to three different planes, and only one peak in focus is captured in a camera. The performance of the modified SA-based filter has been studied in comparison to the conventional SA filter as well as with other filters.     

Detection performance of wavelet-based joint transform correlation

The detection performance of a wavelet-based joint transform correlator (JTC) is studied by use of two types of images with different spatial-frequency contents and contrast. The simulation results show that, in comparison with an amplitude-modulated JTC, the performance for intraclass pattern recognition can be optimized by using a single wavelet filter.     

Temporal detection in human vision: dependence on spatial frequency.

In the study of perception of temporal changes in luminance, it is customary to model perceptual performance as based on one or more linear filters. The task is then to estimate the temporal impulse responses or the representation of the impulse response in the frequency domain. Previously, temporal masking data have been used to estimate the properties and numbers of these temporal mechanisms (filters) in central vision for 1-cycle-per-degree (cpd) targets [Vision Res. 38, 1023 (1998)]. The same methods have been used to explore how properties of the estimated filters change with stimulus contrast energy [J. Opt. Soc. Am. A 14, 2557 (1997)]. We present estimated properties for temporal mechanisms that detect low spatial-frequency patterns. The results indicate that two filters provide the best model for performance when mask contrast is significant. There are also differences between properties for mechanisms that detect signal spatial frequencies of 1 cpd and 1/3 cpd. The sensitivity of the low-pass mechanism relative to the bandpass mechanism is reduced at 1/3 cpd, consistent with previous findings.     

Interferometric optical fourier-transform processor for calculation of selected spatial frequencies

A novel interferometric optical Fourier-transform processor is presented that calculates the complex-valued Fourier transform of an image at preselected points on the spatial-frequency plane. The Fourier spectrum of an arbitrary input image is interfered with that of a reference image in a common-path interferometer. Both the real and the imaginary parts of the complex-valued spectrum are determined. The source and the reference images are easily matched to guarantee good fringe visibility. At least six interferograms are postprocessed to extract the real and the imaginary parts of the Fourier spectrum at preselected points. The proposed hybrid optical-digital technique is computationally appropriate when the number of desired spatial frequencies is small compared with the number of pixels in the image. When the number of desired points is comparable with the number of image pixels, a conventional or pruned two-dimensional fast Fourier transform is more appropriate. The number of digital operations required by the hybrid optical-digital Fourier processor is proportional to the number of desired spatial frequencies rather than the number of pixels in the image. The points may be regularly distributed over the spatial-frequency plane or concentrated in one or several irregularly shaped regions of interest. The interferometric optical Fourier processor is demonstrated in a moving-object trajectory estimation system. The system successfully estimates the trajectory of multiple objects moving over both stationary and white-noise backgrounds. A comparison of performance was made with all-digital computation. With everything else equal, our hybrid optical-digital calculation was more than 3 orders of magnitude faster.     

Experimental verifications of a joint transform correlator using compressed reference images

Single-target and multiple-target detections by using a joint transform correlator (JTC) with compressed reference images are experimentally verified. Two high-contrast images with different spatial-frequency content are used as test scenes. Although an effect of the additive noise on detection performance of the proposed correlator is more severe than that of the compression, the experimental results confirm the feasibility of implementing the JTC with compressed reference images.     

Spatial-frequency Fourier polarimetry of human blood plasma in the diagnostics of pathological changes

A method of polarization mapping of the optical-anisotropic polycrystalline networks of the blood plasma albumin and globulin proteins with adjusted spatial-frequency filtering of the coordinate distributions of the azimuth and ellipticity of the polarization of laser radiation in the Fourier plane is proposed and substantiated. A set of criteria of diagnosing prostate cancer based on the statistical correlation and fractal analysis of the spatial-frequency filtered polarization distributions generated by dendritic networks of albumin and globulin spherulitic networks has been detected and substantiated.     

Spectral optimized asymmetric segmented phase-only correlation filter

We suggest a new type of optimized composite filter, i.e., the asymmetric segmented phase-only filter (ASPOF), for improving the effectiveness of a VanderLugt correlator (VLC) when used for face identification. Basically, it consists in merging several reference images after application of a specific spectral optimization method. After segmentation of the spectral filter plane to several areas, each area is assigned to a single winner reference according to a new optimized criterion. The point of the paper is to show that this method offers a significant performance improvement on standard composite filters for face identification. We first briefly revisit composite filters [adapted, phase-only, inverse, compromise optimal, segmented, minimum average correlation energy, optimal trade-off maximum average correlation, and amplitude-modulated phase-only (AMPOF)], which are tools of choice for face recognition based on correlation techniques, and compare their performances with those of the ASPOF. We illustrate some of the drawbacks of current filters for several binary and grayscale image identifications. Next, we describe the optimization steps and introduce the ASPOF that can overcome these technical issues to improve the quality and the reliability of the correlation-based decision. We derive performance measures, i.e., PCE values and receiver operating characteristic curves, to confirm consistency of the results. We numerically find that this filter increases the recognition rate and decreases the false alarm rate. The results show that the discrimination of the ASPOF is comparable to that of the AMPOF, but the ASPOF is more robust than the trade-off maximum average correlation height against rotation and various types of noise sources. Our method has several features that make it amenable to experimental implementation using a VLC.     

Is Fourier analysis performed by the visual system or by the visual investigator.

A numerical Fourier transform was made of the pincushion grid illusion and the spectral components orthogonal to the illusory lines were isolated. Their inverse transform creates a picture of the illusion. The spatial-frequency response of cortical, simple receptive field neurons similarly filters the grid. A complete set of these neurons thus approximates a two-dimensional Fourier analyzer. One cannot conclude, however, that the brain actually uses frequency-domain information to interpret visual images.     

Gray-level computer-generated hologram filters for multiple-object correlation

Synthesis of gray-level computer-generated holograms allows for an increase of the information storage capability that is usually achieved with conventional binary filters. This is mainly because more degrees of freedom are available. We propose to profit from this feature by synthesizing complex filters formed by many superimposed holograms, each with a different carrier frequency. We apply these gray-level filters to perform multichannel correlation and in this way enhance the capability of optical correlators to process the information in parallel and simultaneously. First, we analyze the behavior of some performance criteria on the impulse response and on the correlation as a function of the number of holograms that are multiplexed. Then we show the results of two experiments: In the first a composed phase-only filter is used in a multiple-object recognition process. In the second a composed synthetic discriminant function filter is used to implement an object classification by means of a binary code.     

Spatial frequency,phase, and the contrast of natural images

We examined contrast sensitivity and suprathreshold apparent contrast with natural images. The spatial-frequency components within single octaves of the images were removed (notch filtered), their phases were randomized, or the polarity of the images was inverted. Of Michelson contrast, root-mean-square (RMS) contrast, and band-limited contrast, RMS contrast was the best index of detectability. Negative images had lower apparent contrast than their positives. Contrast detection thresholds showed spatial-frequency-dependent elevation following both notch filtering and phase randomization. The peak of the spatial-frequency tuning function was approximately 0.5-2 cycles per degree (c/deg). Suprathreshold contrast matching functions also showed spatial-frequency-dependent contrast loss for both notch-filtered and phase-randomized images. The peak of the spatial-frequency tuning function was approximately 1-3 c/deg. There was no detectable difference between the effects of phase randomization and notch filtering on contrast sensitivity. We argue that these observations are consistent with changes in the activity within spatial-frequency channels caused by the higher-order phase structure of natural images that is responsible for the presence of edges and specularities.     

角振幅的图像测量方法

将时间平均成像方法用于谐波角振动物体的振幅测量。采用该方法只需用普通的CCD摄像机分别摄取被测物体的静态下在图像及其在谐波振动状态下的一幅时间平均成像,即可求得该物体的角振幅。为求解该问题所导出的非线性方程,本文构造了基于图像相关的迭代算法。实验表明该测量方法具有较高的精度和工程可用性,且对实验设备和测量环境要求不高,很适合现场测量。     

Intraclass and between-class training-image registration for correlation-filter synthesis

Correlation filters have traditionally been designed without much attention given to the issue of the training images within a class or the relative spatial position between classes. We examine the impact of training-set registration on correlation-filter performance and develop techniques for centering the training images from a class that result in improved performance. We also show that it is beneficial to adjust the spatial position of the classes relative to one another. Although the proposed techniques are relevant for many types of correlation filter, we limit our discussion to algorithms for the maximum average correlation height filter and the distance classifier correlation filter.     

Evaluation of the impact of finite-resolution effects on scintillation compensation using two deformable mirrors.

The impact of finite-resolution deformable mirrors and wave-front sensors is evaluated as it applies to fullwave conjugation using two deformable mirrors. The first deformable mirror is fixed conjugate to the pupil, while the second deformable mirror is at a finite range. The control algorithm to determine the mirror commands for the two deformable mirrors is based on a modification of the sequential generalized projection algorithm. The modification of the algorithm allows the incorporation of Gaussian spatial filters into the optimization process to limit the spatial-frequency content applied to the two deformable mirrors. Simulation results are presented for imaging and energy projection scenarios that establish that the optimal spatial filter waist to be applied is equal to the subaperture side length in strong turbulence. The effect of varying the subaperture side length is examined, and it is found that to effect a significant degree of scintillation compensation, the subapertures, and corresponding spacing between actuators, must be much smaller than the coherence length of the input field.     

Automatic target recognition employing signal compression

Quadratic correlation filters (QCFs) have been used successfully to detect and recognize targets embedded in background clutter. Recently, a QCF called the Rayleigh quotient quadratic correlation filter (RQQCF) was formulated for automatic target recognition (ATR) in IR imagery. Using training images from target and clutter classes, the RQQCF explicitly maximized a class separation metric. What we believe to be a novel approach is presented for ATR that synthesizes the RQQCF using compressed images. The proposed approach considerably reduces the computational complexity and storage requirements while retaining the high recognition accuracy of the original RQQCF technique. The advantages of the proposed scheme are illustrated using sample results obtained from experiments on IR imagery.     

Separation of the first-order image of the particle field in off-axis focused-image holography

The separation of multiple images is considered in the context of designing holographic image-focused particle diagnostic systems. Two techniques have been employed to determine the minimal directional cosine of the reference wave that ensures the separation of the first-order image of the particle field from the higher-order undesired images. The first approach is based on tracing the rays through the reconstructed images of the particles situated within the sample volume, whereas the second approach relies upon the analysis of the spectra of the reconstructed waves in the spatial-frequency domain. The results obtained by these techniques are compared and discussed.     

Recognition of diffuse liver cirrhosis based on image analysis

This paper presents non-invasive method for diagnosis of diffuse liver cirrhosis using ultrasound images. There are three main contributions of our detection method. The first contribution of this method is based on selection of multiple regions of interest (ROIs) with dynamic sizes in liver tissue. The use of multiple ROIs significantly achieves low computations that are required to classify the liver. The number of ROIs is variable and is optimised to achieve the best results. Then, simple but efficient features are extracted from each ROI. The second one is to apply a voting classification with use of multiple ROIs. The third one is to optimise the automatic selection of the parameters using the genetic algorithm. The proposed method has a higher performance compared to other research work and the obtained results show that the recognition accuracy is of 80.77%.     

Optical correlation of images with signal-dependent noise using constrained-modulation filter devices

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-? correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technlogy. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.     

Simulation of IR images of natural backgrounds

Two schemes for the simulation of IR images of ground terrain are presented. Both preserve the statistics and power spectra of the temperature variation over the scene according to the experimental findings. The first scheme generates the scene directly in the spatial domain, while the second generates it in the spatial-frequency domain. Each is advantageous according to the simulation task needed.