Abstract

We propose a new algorithm for estimating the location of an object in multichannel images when the noise is spatially disjointed from (nonoverlapping with) the target. This algorithm is optimal for nonoverlapping noise and for multichannel images in the maximum-likelihood sense. We consider the case in which the statistical parameters of the input scene are unknown and are estimated by observation. We assess the results for simulated images with white and Gaussian background, for a large scale of variances of the background noise, and different values of the contrast in the scene. We compare the results of this algorithm with the results obtained with two other algorithms, the optimal algorithm for monochannel nonoverlapping noise and the optimal algorithm for multichannel additive noise, and we show that in both cases improvement can be obtained. We show the efficiency of the estimation for real input scenes when the background noise is correlated clutter noise. This algorithm has the same complexity as correlation, and the improvement is obtained with no more calculation cost than with classic methods.

© 2000 Optical Society of America

Detection theory approach to multichannel pattern location

M. Guillaume, Ph. Réfrégier, J. Campos, and V. Lashin
Opt. Lett. 22(24) 1887-1889 (1997)

Accuracy of location measurement of a noisy target in a nonoverlapping background

Vitaly Kober and Juan Campos
J. Opt. Soc. Am. A 13(8) 1653-1666 (1996)

Optimum filter for detection of a target in nonoverlapping scene noise

Bahram Javidi and Jun Wang
Appl. Opt. 33(20) 4454-4458 (1994)

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

Bahram Javidi and Jun Wang
J. Opt. Soc. Am. A 11(10) 2604-2612 (1994)

Error probability of an optimum receiver designed for nonoverlapping target and scene noise

Amir H. Fazlollahi and Bahram Javidi
J. Opt. Soc. Am. A 14(5) 1024-1032 (1997)