Autofocus Method for Digital Holographic Reconstruction of Microscopic Object

Abstract

The detection of focus plane is the key of numerical reconstruction of wavefront in digital micro-holography. In this paper, three autofocusing evaluation functions, variance, Fourier spectrum and standard deviation correlation, are analyzed and demonstrated based on experimental investigation. By using an US Air Force test target as the microscopic object, the three autofocusing evaluation functions are compared and analyzed based on Fresnel and angular spectrum algorithms, including unimodality, sharpness, veracity, distance range and computing time. The results show that there are better unimodality near the focused image plane for all the three autofocusing evaluation functions, and the same focused position is obtained by these algorithms. Fourier spectrum algorithm is the optimal one in digital holographic microscopy because of its most time-efficiency. Fresnel transform algorithm can be absolutely used to digital holographic autofocusing. Moreover, the focusing computation time can be decreased dramatically by choosing part of the reconstructed image as the focusing evaluation area. method, which is done in the reconstruction process only by computer procedure. The key of the digital holographic autofocusing is focusing evaluation function. Recent year, many focusing evaluation functions have been proposed (8-11), but most of them are applied to the on-axis digital holography. The studies of the evaluation functions that can be used to off- axis Fresnel digital holography with pre-magnification based on the Fresnel transform algorithm have not been reported up to now. In this paper the performance of the three functions are testified and compared experimentally firstly. Then the focusing evaluation method based on the part of the entire image plane is studied.