Design of filters to detect a noisy target in nonoverlapping background noise

Two types of filter are proposed to detect a noisy target embedded in nonoverlapping background noise by optimization of two proposed criteria that are used in the assessment of filter design and performance. Criterion 1 is defined as the ratio of the square of the expected value of the correlation-peak amplitude to the expected value of the output-signal energy. Criterion 2 is defined as the ratio of the square of the expected value of the correlation-peak amplitude to the average output-signal variance. It is shown that, for the nonoverlapping target and scene noise models, the target window and the scene noise window affect the filter functions significantly. Computer-simulation tests of the generalized optimum filter for various kinds of noisy input image are provided to investigate filter performance in terms of peak-to-output-energy ratio, discrimination against undesired objects, and tolerance to target distortion (for example, target rotation and scaling). We compare the results with those of other filters to verify the performance of the optimum filters.

[1]  B. V. Vijaya Kumar,et al.  Minimum-variance synthetic discriminant functions , 1986 .

[2]  D. Casasent,et al.  Minimum noise and correlation energy optical correlation filter. , 1992, Applied optics.

[3]  B. Kumar,et al.  Performance measures for correlation filters. , 1990, Applied optics.

[4]  Bahram Javidi,et al.  Minimum mean-square-error filter for pattern recognition with spatially disjoint signal and scene noise , 1993 .

[5]  Bahrain Javidi,et al.  Performance of the nonlinear joint transform correlator for images with low-pass characteristics. , 1994, Applied optics.

[6]  D. Casasent,et al.  Minimum average correlation energy filters. , 1987, Applied optics.

[7]  H J Caulfield,et al.  Improved discrimination in optical character recognition. , 1969, Applied optics.

[8]  D. Casasent,et al.  Position, rotation, and scale invariant optical correlation. , 1976, Applied optics.

[9]  J. Horner,et al.  Fourier optical signal processors , 1989, Proc. IEEE.

[10]  B Javidi,et al.  Limitation of the classic definition of the correlation signal-to-noise ratio in optical pattern recognition with disjoint signal and scene noise. , 1992, Applied optics.

[11]  J L Horner,et al.  Pattern recognition with binary phase-only filters. , 1985, Applied optics.

[12]  G. Turin,et al.  An introduction to matched filters , 1960, IRE Trans. Inf. Theory.

[13]  B Javidi,et al.  Optimum receiver design for pattern recognition with nonoverlapping target and scene noise. , 1993, Optics letters.

[14]  A. B. Vander Lugt,et al.  Signal detection by complex spatial filtering , 1964, IEEE Trans. Inf. Theory.

[15]  J L Horner,et al.  Metrics for assessing pattern-recognition performance. , 1992, Applied optics.

[16]  J. Horner,et al.  Phase-only matched filtering. , 1984, Applied optics.

[17]  B Javidi,et al.  Generalization of the linear matched filter concept to nonlinear matched filters. , 1990, Applied optics.