Autofocusing method for Fresnel zone aperture coded image

Fresnel zone aperture (FZA) lensless imaging encode the incident light into hologram-like pattern, so that the scene image can be refocused by back propagation method. However, the inherent twin image and inaccuracy focusing distance degrade the imaging quality. This brings difficulties for the target classification and recognition applications. We proposed a high-quality reconstruction and autofocusing method for FZA lensless imaging. By investigating the image sharpness metrics on the back propagation images, the accuracy focusing distance could be estimated. Total variation regularization based alternating direction method of multipliers algorithm is proposed to suppress the twin image existing in the back propagation reconstruction. Experimental results show that the proposed method can significantly improve the target recognition rate from 4.06% to 90.00%.