Correlation Peak Intensity Research Articles

Self-Organization of Polystyrene-b-polyacrylic Acid (PS-b-PAA) Monolayer at the Air/Water Interface: A Process Driven by the Release of the Solvent Spreading.

We present an in situ structural study of the surface behavior of PS-b-PAA monolayers at the air/water interface at pH 2, for which the PAA blocks are neutral and using N,N-dimethyformamide (DMF) as spreading solvent. The surface pressure versus molecular area isotherm shows a perfectly reversible pseudoplateau over several cycles of compression/decompression. The width of such plateau enlarges when increasing temperature, conversely to what is classically observed in the case of an in-plane first order transition. We combined specular neutron reflectivity (SNR) experiments with contrast variation to solve the profile of each block perpendicular to the surface with grazing-incidence small-angle scattering (GISAXS) measurements to determine the in-plane structure of the layer. SNR experiments showed that both PS and PAA blocks remain adsorbed on the surface for all surface pressure probed. A correlation peak at Q(xy)* = 0.021 Å(-1) is evidenced by GISAXS at very low surface pressure which intensity first increases on the plateau. When compressing further, its intensity decays while Q(xy)* is shifted toward low Q(xy). The peak fully disappears at the end of the plateau. These results are interpreted by the formation of surface aggregates induced by DMF molecules at the surface. These DMF molecules remain adsorbed within the PS core of the aggregates. Upon compression, they are progressively expelled from the monolayer, which gives rise to the pseudoplateau on the isotherm. The intensity of the GISAXS correlation peak is set by the amount of DMF within the monolayer as it vanishes when all DMF molecules are expelled. This result emphizes the role of the solvent in Langmuir monolayer formed by amphiphilic copolymers which hydrophobic and hydrophilic parts are composed by long polymer chains.

Target Recognition Technology Based on Wavelet Transform

Hybrid optoelectronic joint transform correlator is a very effecitve tool to recognize a target, which has important application in military and industry field. However, in actual applications, under some situations, such as complex target background or insufficient contour information etc., the intensity of correlation peaks will be weak. Sometimes, the weak intensity of correlation peaks can not be recognized by joint transform correlator. Wavelet transform is adopted to process the joint target image. The principles of joint transform correlator and wavelet transform are given in this paper. As an actual example, a tank target is adopted to test the feasibility and effectiveness of this method. From computer simulation, we can get good experimental effect. After wavelet transform of joint target image, the intensity of correlation peaks has been increased obviously. Optical experiments confirm the feasibility and effectiveness of this method further. Amounts of experiments prove wavelet transform can extract the target contour effectively. Based on the principle of the proposed algorithm, the target recognizing rate can be increased to a higher level.

HNCA+, HNCO+, and HNCACB+ experiments: improved performance by simultaneous detection of orthogonal coherence transfer pathways.

Three experiments, BEST-TROSY HNCA+, HNCO+ and HNCACB+ are presented for sequential backbone resonance assignment of (13)C, (15)N labelled proteins. The novelty of these experiments with respect to conventional pulse sequences is the detection of additional orthogonal coherence transfer pathways that results in enhanced sensitivity for sequential correlations without significantly compromising the intensity of intra-residue correlation peaks. In addition, a 2-step phase cycle separates peaks originating from the orthogonal coherence transfer pathways in 2 sub-spectra, thus providing similar information as obtained from performing a pair of sequential and intra-residue correlation experiments.

Distorted Target Recognition Based on Prewitt Operator Combined with MACH Filter

The distorted (scale and rotation etc.) target images and the training images are edge extracted by Prewitt operator. The Maximum Average Correlation Height filter is synthesized with the training images. The low frequency information of the distorted target images and the filter is enhanced. Then the edge extracted distorted target image is filtered by the Maximum Average correlation Height filter. Thereby, the distortion tolerance of the Maximum Average Correlation Height filter is expanded. By this method, when the space edge extraction combines with frequency domain filtering, the scale distortion tolerance is 0.76~1.56 times; the rotation distortion tolerance can reach up to 80 degrees. For the targets exceeding the distortion tolerance range, the intensity of correlation peak becomes weaker and weaker, but some of the targets can still be identified.

14N–1H Heteronuclear Multiple-Quantum Correlation Magic-Angle Spinning NMR Spectroscopy of Organic Solids

Abstract 14N–1H heteronuclear multiple-quantum correlation (HMQC) solid-state magic-angle spinning (MAS) NMR spectra recorded at a 1H Larmor frequency of 850 MHz are presented for the dipeptide β-AspAla. A modified version of the pulse sequence presented by Gan et al. (Chem. Phys. Lett. 435 (2007) 163) that utilises rotary resonance recoupling (R3) at the n = 2 condition (ν 1 = 2ν R ) is employed. Spectra recorded with a short recoupling period (under 200 μs) show two correlation peaks corresponding to the NH and NH3 moieties in the dipeptide. The quadrupolar product, P Q = C Q √ [1 + (η Q 2/3)], is determined experimentally as 3.1 MHz (NH) and 1.0 MHz (NH3) by a comparison of the 14N and 15N isotropic chemical shifts which differ due to the isotropic second-order quadrupolar shift for the spin I = 1 14N nucleus. It is shown that the peak sensitivities increase markedly upon increasing the MAS frequency from 30 to 45 to 60 kHz due to a combination of the reduced residual dipolar broadening of the 1H resonances and a lengthening of the coherence lifetimes under R 3 recoupling. Increasing the recoupling period leads to the observation of additional peaks corresponding to longer range intra- and intermolecular NH proximities. Reasonable agreement is evident upon comparing the experimental build-up of correlation peak intensity to that observed for eight-spin density-matrix simulations.

Optical correlator based target detection, recognition, classification, and tracking

A dedicated automatic target recognition and tracking optical correlator (OC) system using advanced processing technology has been developed. Rapidly cycling data-cubes with size, shape, and orientation are employed with software algorithms to isolate correlation peaks and enable tracking of targets in maritime environments with future track prediction. The method has been found superior to employing maximum average correlation height filters for which the correlation peak intensity drops off in proportion to the number of training images. The physical dimensions of the OC system may be reduced to as small as 2 in. × 2 in. × 3 in. (51 mm × 51 mm × 76 mm) by modifying and minimizing the OC components.

Calibration method for inner product calculation by the volume holographic correlator with randomly interleaved images

A volume holographic correlator is capable of inner product calculations between the input image and multiple stored images in parallel. The inner product that is the center value of the correlation can provide a scalar measure of change between two images. The inner product values are directly acquired by measuring the intensities of the correlation peaks on the CCD. However, the measured intensities are not exactly equal to the theoretical inner product values due to the redundancy correlation. The structure of the correlation peak for randomly interleaved images is analyzed. It can be regarded as two volumes, one pyramid and one prism. The relative inner product value is only determined by the height of the pyramid. The prism, caused by the redundancy correlation, appears as the background noise, which is the main source of the inner product calculation error. A calibration method is proposed to remove the prism from the measured intensity. Based on the geometric structure of the correlation peak, the theoretical expression of the inner product value for the pyramid is derived. A white image is employed as the input image and the measured correlation peak intensity is used to calibrate the inner product value. The calibration method can effectively eliminate the error caused by the redundancy correlation to achieve a high output accuracy of the volume holographic correlator. Experiments are demonstrated for the validity of the method.

基于多小波变换的红外目标探测与识别

Considering the practical application of target recognition with optoelectronic joint transform correlator,the infrared image detected was processed by multiwavelet transform,and its edge points were extracted by the method of local modulus maximum.Capturing much contour can improve the capacity of target recognition.The multiwavelet functions usually used to infrared target processing are GHM and SA4.Simulation experiments show that the correlation output of edges extracted by GHM is obviously better than that one of edges extracted by SA4,because the former edges carry much contour of image.Compared to the optical correlation detection result of original image with that of edge image extracted by GHM,it is found that the latter effectively enhances the intensity of correlation peaks.

Shift and scale‐invariant correlation for pattern recognition based on the bidimensional empirical mode decomposition with noise robustness

A novel filter is proposed to improve the noise robustness and discrimination capability for shift and scale invariant pattern recognition. This filter is a combination of mellin radial harmonic filter (RHF) and the bidimensional empirical mode decomposition. The basic principle of this method is to make use of partial reconstructions of the image by the relevant intrinsic mode functions corresponding to the most important structures of the image. A criterion is proposed to determine the proper number of intrinsic mode functions to be discarded for denoising by discussing the characteristic of the noise. The proposed filter provides a wider allowable scale change of the object. Within this range, the correlation peak intensity is relatively uniform even in the case of noise. This proposed filter has been tested experimentally to confirm the result from numerical simulations for cases with and without additive white Gaussian noise.

Three-Dimensional Color Pattern Recognition Using Fringe-Adjusted Joint Transform Correlation With CIELab Coordinates

A new 3-D color pattern recognition technique, utilizing the concept of a fringe-adjusted joint transform correlator (JTC) and CIELab color space, is proposed in this paper. The proposed technique yields better discrimination capability and sharper and stronger correlation peak intensity as compared with a classical JTC with conventional red-green-blue (RGB) components. Simulation results are presented to verify the robustness of the proposed technique.

Simultaneous use of amplitude and phase to improve the validation process in a joint transform correlator

We present an alternative technique to enhance the discrimination performance in a JTC architecture, employed as a validation procedure. We define as complex objects those amplitude objects bonded to random phase masks. When using complex objects as reference inputs in a JTC optical validation system, correlation peak intensity and correlation peak shape become simultaneous key parameters to increase the discrimination ability of the system. Simulation results, comparing amplitude-only objects versus complex objects as inputs to the system, reveal the validity of our approach and show the sensitivity of the JTC architecture to the additional phase structures.

Scale-invariant pattern recognition using a combined Mellin radial harmonic function and the bidimensional empirical mode decomposition

A novel scale and shift invariant pattern recognition method is proposed to improve the discrimination capability and noise robustness by combining the bidimensional empirical mode decomposition with the Mellin radial harmonic decomposition. The flatness of its peak intensity response versus scale change is improved. This property is important, since we can detect a large range of scaled patterns (from 0.2 to 1) using a global threshold. Within this range, the correlation peak intensity is relatively uniform with a variance below 20%. This proposed filter has been tested experimentally to confirm the result from numerical simulation for cases both with and without input white noise.

Enhancing the capabilities of binary phase only filter

In this paper, we demonstrate that the capabilities of a binary phase-only filter (BPOF) can be enhanced to identify targets irrespective of rotation, scale or the imaging spectral band by utilizing the concept of log-polar transform and image fusion. Till date, BPOFs have been considered to be the simplest of all filters and incapable of identifying distorted images or images of different spectral bands like the visible or infrared (IR) bands. The novelty of this work lies in the approach adopted to demonstrate that a BPOF is equally capable of distortion-invariance like any other distortion-invariant complex matched filter. This is done by suitably fusing the images of visible and IR bands and then taking the log-polar transformation of the fused image to synthesize the BPOF. A single BPOF is thus sufficient to identify (0–360)° in-plane rotated images, (50–190)% scaled images, combination of rotation and scale changes of the target, noisy image of both the visible and IR spectral bands. A further enhancement of the correlation peak intensity (CPI) is achieved by modifying this BPOF with Mexican-hat wavelet. The designed filter was implemented in the hybrid digital–optical correlation scheme. Correlation peak intensity and peak correlation energy (PCE) have been calculated as metrics of goodness of the proposed approach. Experimental results have been presented.

Joint fractional transform correlator based on structured light coding

A new method for 3-D object recognition is proposed. The method combines structured light coding with the joint fractional transform correlator (JFrTC).When projecting sinusoidal grating fringes onto the surface of 3-D objects, the fringes are distorted due to the height of the objects. Then the distorted fringe patterns are regarded as the joint input image used for correlation recognition. Simultaneously, to achieve JFrTC, we can replace either (or both) Fourier transforms in the joint transform correlator (JTC) by a fractional Fourier transform. Four architectures of JFrTC with the distorted fringe pattern and four JFrTC with the intensity map are analyzed in detail. By comparing these different structures, a JFrTC with distorted fringe patterns, especially for the FrT-FT architecture, is suggested to improve the discernment performance, to more decrease the widths of the correlation peaks, and to flexibly change the intensity and position of correlation peaks. Both mathematical analysis and computer simulation results are presented in support of the proposed idea.

Spectral band independent recognition in a differential binary joint transform correlator

Images of a target in a specific spectral band in general show no correlation with images of the same target in a different spectral band. Hence in a joint transform correlator (JTC) architecture, if the reference and input target are the images captured through a visible (e.g., charge-coupled device or CCD camera) and infrared (IR) detector, autocorrelation peaks are not obtained. This drawback has been overcome in this paper by the use of a CCD–IR fused image as the reference image. Daubechies wavelet transform, which produces the least root-mean-square (RMS) error in the fusion process in comparison to other wavelets, has been used for the purpose. A comparative analysis of the proposed idea has been carried out for the classical JTC (CJTC), binary JTC (BJTC) and differential binary JTC (DBJTC) algorithms. Since the DBJTC removes the dc completely and produces sharp correlation peaks compared to the other techniques, computer simulation and experimental results are shown for the proposed idea using DBJTC. The same fused reference image has also been used to identify multiple targets in a scene using DBJTC. Performance measures like correlation peak intensity (CPI), dc/ac and peak correlation energy (PCE) have been calculated as metrics of goodness for the proposed scheme.

Spectral band invariant wavelet-modified MACH filter

Filters synthesized with images of a specific spectral band in general fail to recognize targets in a different spectral band. In this paper, we therefore demonstrate the use of the wavelet-modified maximum average correlation height (WaveMACH) filter for automatic target recognition applications in both the visible and infrared (IR) spectral bands. As any input target appears different when imaged through two different sensors, i.e., a CCD or an IR camera, a WaveMACH filter synthesized using a CCD image shows no correlation with the image of the same target from an IR camera and vice-versa. Hence, separate filters are required to match the input targets from the two sensors. To avoid the synthesis and storage of separate filters, the images from CCD and IR camera are fused using Daubechies wavelet and then the rotation-invariant WaveMACH filter generated with the fused image. In all, 18 WaveMACH filters (each of 20° range) are required for in-plane rotation invariance in both the spectral bands for the full range of 0–360°. Computer simulation and experimental results implemented in hybrid digital–optical correlator architecture are shown for the proposed idea. The same filters have also been used to identify multiple targets in a scene. Performance measures like peak-to-sidelobe ratio (PSR), peak correlation energy (PCE) and correlation peak intensity (CPI) have been calculated as metrics of goodness.

Two-beam-coupling correlator for synthetic aperture radar image recognition with power-law scattering centers preenhancement

Synthetic radar image recognition is an area of interest for military applications including automatic target recognition, air traffic control, and remote sensing. Here a dynamic range compression two-beam-coupling joint transform correlator for detecting synthetic aperture radar targets is utilized. The joint input image consists of a prepower-law, enhanced scattering center of the input image and a linearly synthesized power-law-enhanced scattering center template. Enhancing the scattering center of both the synthetic template and the input image furnishes the conditions for achieving dynamic range compression correlation in two-beam coupling. Dynamic range compression (a) enhances the signal-to-noise ratio, (b) enhances the high frequencies relative to low frequencies, and (c) converts the noise to high frequency components. This improves the correlation-peak intensity to the mean of the surrounding noise significantly. Dynamic range compression correlation has already been demonstrated to outperform many optimal correlation filters in detecting signals in severe noise environments. The performance is evaluated via established metrics such as peak-to-correlation energy, Horner efficiency, and correlation-peak intensity. The results showed significant improvement as the power increased.

Holographic Interferometer as a Correlator of Phase Distortions with Response in the Form of Interference Pattern

Considered in the work are known properties of holographic interferometer as according to the correlator with output signal in the form of interference fringes. It is known that a space correlation has various ratios of intensity between central correlation peak and background part for objects with different phase microrelief of a surface. Correspondingly an interference pattern must have different space distribution of contrast. A magnitude of contrast depends on changes in distribution of microrelief of investigated object, whereas the interference pattern depends on macroscopic modification of a form of the object. Used here is a scheme of Fourier holography with a random phase modulator in signal beam, reference beam is a point source, and restoring beam is the random phase modulator with random phase shift against initial random phase modulator. Also investigated is a recording of holographic interferogram with these random phase modulators. As the results of original theoretical consideration there was obtained an expression for fringe contrast and intensity of correlation peak. This model was tested by simulating of forming of holographic interferogram and reconstruction of the cross-correlation peak with phase distortions of various statistical distributions. Compared here are theoretical results, simulation results, and results obtained in real experiment.

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.

Wavelet-modified fringe-adjusted joint transform correlator

In this paper, we implement a wavelet-modified fringe-adjusted joint transform correlator (JTC) for real-time target recognition applications. In real-time situation the input scene is captured using a charge-coupled device (CCD) camera. The obtained joint power spectrum is multiplied by a pre-synthesized fringe-adjusted filter and the resultant function is processed with an appropriately scaled wavelet filter. Three performance measure parameters: correlation peak intensity, peak-to-sidelobe ratio, and signal-to-clutter ratio have been calculated for fringe-adjusted joint transform correlator (FJTC) and wavelet-modified fringe-adjusted joint transform correlator (WFJTC). The WFJTC has been found to yield better results in comparison to conventional FJTC. To suppress the undesired strong dc, the resultant function is differentiated. Differential processing wavelet-modified fringe-adjusted joint power spectrum removes the zero-order spectra and hence improves the detection efficiency. To focus the correlation terms in different planes in order to capture one of the desired autocorrelation peaks and discard the strong dc and another autocorrelation peak, chirp-encoding technique has also been applied. Targets with Gaussian and speckle noise have also been used to check the correlation outputs. Computer simulation and experimental results are presented.