Optimal multichannel estimation of the location of a target with nonoverlapping noise

We propose a new algorithm for estimating the location of an object in mult ichannel images when the noise is spatially disjointed from (nonoverlapping with) the target. This algorithm is optimal for nonoverlapping noise and f or multichannel images in the maximum-likelihood sense. We consider the cas e in which the statistical parameters of the input scene are unknown and ar e estimated by observation. We assess the results for simulated images with white and Gaussian background, for a large scale of variances of the backg round noise, and different values of the contrast in the scene. We compare the results of this algorithm with the results obtained with two other algo rithms, 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. me show the efficiency of the estimatio n for real input scenes when the background noise is correlated clutter noi se. This algorithm has the same complexity as correlation, and the improvem ent is obtained with no more calculation cost than with classic methods. (C ) 2000 Optical Society of America [S0740-3232(00)00111-3] OCIS codes: 330.0 330, 100.0100.