Daniel W. Carlson

Optimal trade-off synthetic discriminant function filters for arbitrary devices

A new correlation-filter design methodology is presented for achieving two objectives: synthetic discriminant function filters that can be implemented on arbitrary various criteria of interest. devices and that can provide optimal trade-off among various criteria of interest.

Distance classifier correlation filters

The performance of shift-invariant distance classifiers based on correlation filters is evaluated. First, the effect of noise on a classifier designed to recognize synthetic aperture radar (SAR) is observed. Then, a 2-class ATR designed to recognize infrared images of actual targets is evaluated. The results attest to the ability of the distance classifier to tolerate distortions, and recognize targets in the presence of noise and clutter.

Optimal trade-off distance classifier correlation filters (OTDCCFs) for synthetic aperture radar automatic target recognition (SAR ATR)

Recent developments in optimal trade-off based composite correlation filter methods have improved the recognition and classification of an object over a range of image distortions. We extend the capability of the distance classifier correlation filter introduced by Mahalanobis et al by using he optimal trade-off between different correlation criteria. These correlation filters can be used for the automatic target cueing or recognition of synthetic aperture radar (SAR) images. In this paper we will present results of designing these distortion-tolerant filters with simulated SAR imagery and testing with simulated SAR target images inserted into real SAR backgrounds.

Tradeoffs in the design of correlation filters

Designing filters for use with optical correlators is really an exercise in trading one performance measure against another. In this critical review, we present several different situations where such a tradeoff is carried out. An informed understanding of this law of nature is important in making sure that our goals in optical pattern recognition are realistic.

Bias in correlation peak location

Even in the absence of input noise, there is no guarantee that correlation peaks resulting from some filters such as the binary phase-only filters (BPOFs) will be at the origin when the input is the reference object centered. Simulation results are included that show this peak shift is usually negligible.

Efficient determination of the optimum gain and angle in the design of optical correlation filters

In designing optimal correlation filters for implementation on arbitrary spatial light modulators, we need to determine two parameters (a gain and an angle) to maximize the performance criterion of interest. We present a method to find these optimal gain and angle parameters directly.

Optimal correlation filters for implementation on deformable mirror devices

A systematic procedure is presented for designing optimal correlation filters for implementation on deformable mirror devices (DMDs) exhibiting cross-coupled amplitude and phase characteristics. The utility of the algorithm for designing such filters is illustrated using five different device characteristics: phase-only filter, a binary phase-only filter, a diagonal line characteristic, a DMD zeroth-order characteristic, and a DMD first-order characteristic. Results are also presented regarding the signal-to-noise ratio and peak-to-correlation energy obtainable using these filters. The performance achievable using DMD type characteristics was found to be close to that of phase-only filter.

Composite correlation filters for SAR image recognition

Recent developments in composite correlation filter methods have improved the recognition and classification of an object over a range of image distortions. These correlation filters can be used for the automatic target cueing or recognition images. These new filter methods can be optimized for different correlation criteria in order to improve the recognition capability of the filter. In this paper we will present results of designing these distortion- tolerant correlation filters with simulated SAR imagery and testing with real and simulated SAR targets.

Synthetic discriminant functions for implementation on arbitrarily constrained devices

The conventional Synthetic Discriminant Function (SDF) filters are complex-valued and thus cannot be accommodated on spatial light modulators that can represent only a subset of all possible values in the complex plane. Here, we compare the performance of different SDF filters designed to satisfy certain device restrictions.

MEDOF 3.0: optimizing composite filters in the presence of device constraints and system noise

For optical implementation of correlation filters, we must design filters that can be implemented on available spatial light modulators (SLMs). Previous versions of computer code MEDOF: minimum Euclidean distance optimal filter produced various correlation filters using a single training image. In the newest version of MEDOF, we can use a training set of images to generate composite filters that include system noise and device constraints. In this paper we present implementation issues and results using composite filters generated by MEDOF.