Abstract
Optimum multisensor data fusion is addressed for image change detection based on the optimum likelihood ratio test for the statistical dependence of the luminance signals in additive Gaussian noise. It is demonstrated that the information to be transmitted from the sensors to the fusion center is the maximum likelihood estimates of the correlation coefficients between pairs of consecutive image frames. Experimental results illustrate that the detection error decreases as the number of sensors and/or frames increases. >
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