Adaptive matched filter for implicit-target recognition: Application in three-dimensional reconstruction

The design of matched filters for optical correlators requires explicit knowledge of the shape of the target. This requirement limits its usefulness in applications where the appearance of the target is unspecified or dynamically changing. This research presents the design of an adaptive correlation filter by the optimization of the mean-squared-error criterion when the shape of the target is implicit and embedded on a cluttered background with unknown statistics in the reference image. For this, estimators to obtain the region of support of the target as well as statistical parameters of additive and nonoverlapping noise of the scene are proposed. The performance of the proposed filter is analyzed in terms of detection efficiency and location accuracy of an implicit target in the context of stereo matching and three-dimensional reconstruction.