科研之友
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摘要
The capacity of computational ghost imaging (CGI) in depth imaging is usually demonstrated by the technique of time-of-flight. However, this capacity could also be achieved by evaluating the degree of defocus in a reconstructed image. To be more precise, an in-focus image in CGI will be obtained if the propagation distance of the patterns in the virtual reference path matches the practical depth of the object, otherwise a defocused image will be reconstructed. This method usually requires forming the images at all the axial locations (the number of the locations: N), which reduces the efficiency of CGI. In this paper, an auto-focusing method is proposed in the deep-Fresnel (DF) region. We present a new iterative algorithm for performing CGI which evaluates reconstructed images based upon deviation-based correlation. We demonstrate that in a given system, an in-focus image of the object and its depth can be obtained in log(2)N iterations with a depth error e(d )<= delta z (delta z: longitudinal coherence length of the speckle in the DF region). Compared to the conventional method, this approach improves the convergence speed significantly. We believe our work favors the use of CGI in depth-imaging systems.
