Target Identification from Coded Diffraction Patterns via Template Matching

Traditional target detection techniques have been developed using measurements from the object acquired by optical systems that are only able to measure its intensity, losing its optical phase information. The optical phase, for instance, allows describing the shape and depth of an object. This work proposes a target identification methodology that operates over measurements acquired through an optical system that collects coded diffraction patterns (CDP). In contrast to traditional detection techniques, the proposed methodology is able to incorporate the optical phase information of an object as a discriminant in the target detection task. The proposed methodology consists of two steps: first, an estimation of the scene from the acquired CDP is accomplished, second, a scanning procedure with a reference pattern over the estimated scene is performed. Numerical results show that the phase information can be used as an identification discriminant for target detection. Also, simulations demonstrate that the proposed methodology is able to identify a target under highly noisy scenarios using one single snapshot with a success rate up of 84%. Furthermore, it is worth to mention that to the best of our knowledge this is the first methodology that uses the optical phase of an object as a target identification discriminant.