Target tracking has a wide application in varieties of domains and has a rapid development at home and abroad, so the research on target tracking is more valuable in recent years. In this paper hybrid optoelectronic joint transform correlator (HOJTC) is implemented for tracking the target, which is considered as one of the most effective methods. But in practical application, the low contrast character of the target and the moving distortion problems between the target and the template may cause the phenomenon of low recognition ratio of HOJTC. In order to solve this problem, a kind of wavelet-based threshold segmentation method is applied to increase the contrast. Through this algorithm the histogram of the image is firstly decomposed into wavelet coefficients at every scale with wavelet basis function Sym4. And then according to segmentation norm and wavelet coefficients, the thresholds can be chosen from the reconstructed histogram. Finally use these thresholds to segment the image into ideal areas. In addition, for the moving distortion problem, taking temporal state of the target as the template can realize the template update. To prove this method, many tracking experiments of low contrast targets have been performed with optical correlation method. As an example a low contrast target “tank” (the gray contrast is less than 2%) is presented. The tracking result shows that the brightness of the correlation peaks is enhanced and the target recognition ratio is increased. The conclusion can be drawn that applying this algorithm in optical correlation method can implement the low contrast target tracking successfully and this algorithm provides an available solution to low contrast target tracking.
