The Experts below are selected from a list of 273 Experts worldwide ranked by ideXlab platform

Yunlong Sheng - One of the best experts on this subject based on the ideXlab platform.

  • Continuous scale invariant optical composite wavelet Matched Filters with adaptive wavelets
    Wavelet Applications II, 1995
    Co-Authors: Danny Roberge, Yunlong Sheng
    Abstract:

    The wavelet transform (WT) can be used for pattern recognition. One scheme is to extract the wavelet features in the 4-D space-scale joint representation of the 2-D pattern for statistical pattern recognition. Another scheme is the wavelet Matched Filters (WMF), that uses the WT to enhance the edge features and make correlation between the WT of the input image and the WT of the reference image. This approach uses the optical shift invariant continuous WT and implements the WT and the matching of two WTs in a single step of the correlation. Several adaptive WTs and the matching pursuits have been proposed that use the best basis functions to the signal decomposition. The basis is selected from a library of dictionary waveforms to minimize an energy or an entropy in such a way that the signal expansion with those bases is the best for signal representation or classification. Pattern recognition emphasizes the classification. Fast numerical algorithms are given for the signal expansion with the best adaptive discrete orthogonal bases. Most approaches use a fixed shape basic wavelet with varying shift and dilation parameters. Szu et al., proposed adaptive wavelets that are linear combination of wavelets, called the `super-wavelet.' The super-wavelets can be continuous and redundant. The shape of the super-wavelets can be adaptively changed for the particular applications. They show the adaptive WT of the 1-D speech signals. In this paper we show the adaptive WT with continuous 2-D wavelets, whose shape is adaptively changed to achieve the pattern recognition invariant to continuous shift and scale changes. We show why such an adaptive WT is needed and how to construct the composite wavelet Matched filter (CWMF) with the adaptive super-wavelet for the continuous scale invariant pattern recognition. The real-time complex valued optical Filters implementation is reported in this paper.

  • optical pattern recognition with the real time phase only Filters and wavelet Matched Filters
    Second International Conference on Optoelectronic Science and Engineering '94, 1994
    Co-Authors: Yunlong Sheng, Danny Roberge, Luiz Goncalves Neto, Lixin Shen, Gilles Paulhus
    Abstract:

    The spatial light modulator (SLM) is a key element of an optical processor. The limitations of the currently availableSLM's are their limited phase and amplitude modulation capacity, limited space bandwidth product (SBWP) and limited speed.We use the commercial liquid crystal television (LCTV) as a SLM and build a real-time on-axis phase-only opticai correlator.This approach permits efficient use of the SBWP of the SLM (200 x 200 and 440 x 480 for new type of LCTV) and provideshigh light efficiency"2. Various continuous phase-only holograms, Matched Filters, circular harmonic Filters and composite Filtershave been implemented with this coupled mode modulation SLM.

  • Optical composite wavelet-Matched Filters
    Optical Engineering, 1994
    Co-Authors: Danny Roberge, Yunlong Sheng
    Abstract:

    The wavelet-Matched filter performs the continuous wavelet transform for edge feature enhancement and the correlation between two wavelet transforms for pattern recognition in a single step. The composite wavelet-Matched filter is a combination of the wavelet-Matched Filters, that yields desired outputs for a given set of training mages. We present the definition, the iterative design algorithm, the quasi-orthogonality of the components, and the optical implementation of the composite wavelet-Matched filter. The filter yields a sharp correlation peak at the origin without sidelobe. A comparison between the composite wavelet-Matched filter with the conventional composite filter is also given.

  • optical composite wavelet Matched Filters
    SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994
    Co-Authors: Danny Roberge, Yunlong Sheng
    Abstract:

    The composite wavelet-Matched filter is a nonlinear combination of the wavelet-Matched Filters that yields correlation between the wavelet transforms of the input image and a combination of edge enhanced training images. The filter is designed with an iteration algorithm to ensure the desired output peak value for each training image. The filter is optically implemented with a phase mostly modulation liquid crystal television and a photographic amplitude modulation mask. This filter shows the best performance compared with the phase-only composite filter and the conventional composite filter. Experimental results are shown.

  • optical wavelet Matched Filters for shift invariant pattern recognition
    Optics Letters, 1993
    Co-Authors: Yunlong Sheng, Danny Roberge, Harold H Szu
    Abstract:

    We introduce optical wavelet Matched Filters that perform the wavelet transforms for edge enhancement and perform correlations between the wavelet coefficients for shift-invariant pattern recognition. These new bandpass Matched Filters show improved discrimination capability with respect to the conventional Matched spatial filter and improved signal-to-noise ratio with respect to the phase-only Matched filter.

Dan Stamperkurn - One of the best experts on this subject based on the ideXlab platform.

  • simultaneous retrodiction of multimode optomechanical systems using Matched Filters
    Physical Review A, 2020
    Co-Authors: Jonathan Kohler, Justin Gerber, Emma Deist, Dan Stamperkurn
    Abstract:

    Generation and manipulation of many-body entangled states is of considerable interest, for applications in quantum simulation or sensing, for example. Measurement and verification of the resulting many-body state presents a formidable challenge, however, which can be simplified by multiplexed readout using shared measurement resources. In this work, we analyze and demonstrate state retrodiction for a system of optomechanical oscillators coupled to a single-mode optical cavity. Coupling to the shared cavity field facilitates simultaneous optical measurement of the oscillators' transient dynamics at distinct frequencies. Optimal estimators for the oscillators' initial state can be defined as a set of linear Matched Filters, derived from a detailed model for the detected homodyne signal. We find that the optimal state estimate for optomechanical retrodiction is obtained from high-cooperativity measurements, reaching estimate sensitivity at the standard quantum limit (SQL). Simultaneous estimation of the state of multiple oscillators places additional limits on the estimate precision, due to the diffusive noise each oscillator adds to the optomechanical signal. However, we show that the sensitivity of simultaneous multimode state retrodiction reaches the SQL for sufficiently well-resolved oscillators. Finally, an experimental demonstration of two-mode retrodiction is presented, which requires further accounting for technical fluctuations of the oscillator frequency.

Harold H Szu - One of the best experts on this subject based on the ideXlab platform.

  • optical wavelet Matched Filters for shift invariant pattern recognition
    Optics Letters, 1993
    Co-Authors: Yunlong Sheng, Danny Roberge, Harold H Szu
    Abstract:

    We introduce optical wavelet Matched Filters that perform the wavelet transforms for edge enhancement and perform correlations between the wavelet coefficients for shift-invariant pattern recognition. These new bandpass Matched Filters show improved discrimination capability with respect to the conventional Matched spatial filter and improved signal-to-noise ratio with respect to the phase-only Matched filter.

  • wavelet transform as a bank of the Matched Filters
    Applied Optics, 1992
    Co-Authors: Harold H Szu, Yunlong Sheng, Jing Chen
    Abstract:

    The wavelet transform is a powerful tool for the analysis of short transient signals. We detail the advantages of the wavelet transform over the Fourier transform and the windowed Fourier transform and consider the wavelet as a bank of the VanderLugt Matched Filters. This methodology is particularly useful in those cases in which the shape of the mother wavelet is approximately known a priori. A two-dimensional optical correlator with a bank of the wavelet Filters is implemented to yield the time-frequency joint representation of the wavelet transform of one-dimensional signals.

Danny Roberge - One of the best experts on this subject based on the ideXlab platform.

  • Continuous scale invariant optical composite wavelet Matched Filters with adaptive wavelets
    Wavelet Applications II, 1995
    Co-Authors: Danny Roberge, Yunlong Sheng
    Abstract:

    The wavelet transform (WT) can be used for pattern recognition. One scheme is to extract the wavelet features in the 4-D space-scale joint representation of the 2-D pattern for statistical pattern recognition. Another scheme is the wavelet Matched Filters (WMF), that uses the WT to enhance the edge features and make correlation between the WT of the input image and the WT of the reference image. This approach uses the optical shift invariant continuous WT and implements the WT and the matching of two WTs in a single step of the correlation. Several adaptive WTs and the matching pursuits have been proposed that use the best basis functions to the signal decomposition. The basis is selected from a library of dictionary waveforms to minimize an energy or an entropy in such a way that the signal expansion with those bases is the best for signal representation or classification. Pattern recognition emphasizes the classification. Fast numerical algorithms are given for the signal expansion with the best adaptive discrete orthogonal bases. Most approaches use a fixed shape basic wavelet with varying shift and dilation parameters. Szu et al., proposed adaptive wavelets that are linear combination of wavelets, called the `super-wavelet.' The super-wavelets can be continuous and redundant. The shape of the super-wavelets can be adaptively changed for the particular applications. They show the adaptive WT of the 1-D speech signals. In this paper we show the adaptive WT with continuous 2-D wavelets, whose shape is adaptively changed to achieve the pattern recognition invariant to continuous shift and scale changes. We show why such an adaptive WT is needed and how to construct the composite wavelet Matched filter (CWMF) with the adaptive super-wavelet for the continuous scale invariant pattern recognition. The real-time complex valued optical Filters implementation is reported in this paper.

  • optical pattern recognition with the real time phase only Filters and wavelet Matched Filters
    Second International Conference on Optoelectronic Science and Engineering '94, 1994
    Co-Authors: Yunlong Sheng, Danny Roberge, Luiz Goncalves Neto, Lixin Shen, Gilles Paulhus
    Abstract:

    The spatial light modulator (SLM) is a key element of an optical processor. The limitations of the currently availableSLM's are their limited phase and amplitude modulation capacity, limited space bandwidth product (SBWP) and limited speed.We use the commercial liquid crystal television (LCTV) as a SLM and build a real-time on-axis phase-only opticai correlator.This approach permits efficient use of the SBWP of the SLM (200 x 200 and 440 x 480 for new type of LCTV) and provideshigh light efficiency"2. Various continuous phase-only holograms, Matched Filters, circular harmonic Filters and composite Filtershave been implemented with this coupled mode modulation SLM.

  • Optical composite wavelet-Matched Filters
    Optical Engineering, 1994
    Co-Authors: Danny Roberge, Yunlong Sheng
    Abstract:

    The wavelet-Matched filter performs the continuous wavelet transform for edge feature enhancement and the correlation between two wavelet transforms for pattern recognition in a single step. The composite wavelet-Matched filter is a combination of the wavelet-Matched Filters, that yields desired outputs for a given set of training mages. We present the definition, the iterative design algorithm, the quasi-orthogonality of the components, and the optical implementation of the composite wavelet-Matched filter. The filter yields a sharp correlation peak at the origin without sidelobe. A comparison between the composite wavelet-Matched filter with the conventional composite filter is also given.

  • optical composite wavelet Matched Filters
    SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994
    Co-Authors: Danny Roberge, Yunlong Sheng
    Abstract:

    The composite wavelet-Matched filter is a nonlinear combination of the wavelet-Matched Filters that yields correlation between the wavelet transforms of the input image and a combination of edge enhanced training images. The filter is designed with an iteration algorithm to ensure the desired output peak value for each training image. The filter is optically implemented with a phase mostly modulation liquid crystal television and a photographic amplitude modulation mask. This filter shows the best performance compared with the phase-only composite filter and the conventional composite filter. Experimental results are shown.

  • optical wavelet Matched Filters for shift invariant pattern recognition
    Optics Letters, 1993
    Co-Authors: Yunlong Sheng, Danny Roberge, Harold H Szu
    Abstract:

    We introduce optical wavelet Matched Filters that perform the wavelet transforms for edge enhancement and perform correlations between the wavelet coefficients for shift-invariant pattern recognition. These new bandpass Matched Filters show improved discrimination capability with respect to the conventional Matched spatial filter and improved signal-to-noise ratio with respect to the phase-only Matched filter.

Christine M Netishen - One of the best experts on this subject based on the ideXlab platform.

  • radar target identification using spatial Matched Filters
    Pattern Recognition, 1994
    Co-Authors: L M Novak, G J Owirka, Christine M Netishen
    Abstract:

    Abstract The application of spatial Matched filter classifiers to the synthetic aperture radar (SAR) automatic target recognition (ATR) problem is being investigated at MIT Lincoln Laboratory. Initial studies investigating the use of several different spatial Matched filter classifiers in the framework of a 2D SAR ATR system are summarized. In particular, a new application is presented of a shift-invariant, spatial frequency domain, 2D pattern-matching classifier to SAR data. Also, the performance of this classifier is compared with three other classifiers: the synthetic discriminant function, the minimum average correlation energy filter, and the quadratic distance correlation classifier.