Super-resolution imaging and autofocusing via compressive-sensing-based twin-image-free holography

This paper presents an iterative reconstruction framework for super-resolution imaging and autofocusing via compressive-sensing-based twin-image-free holography (SRI-AF-CS-TIFH) for 3D (multi-plane) object in compressed holographic imaging. In our proposed framework, in the first step, the Hough transform edge detection method is incorporated into the eigenvalue-based autofocusing algorithm (dubbed as EIG-AF-Hough) to accurately estimate the focus distances for each plane of multi-plane objects from the snapshot measurements; In the second step, nonlinear optimization is used to achieve the super-resolution reconstruction from the same snapshot measurements. Experimental results demonstrate the effectiveness of our proposed framework for achieving autofocusing and super-resolution in compressed holographic imaging simultaneously in both simulated and real holographic scenarios.