Autofocusing algorithm for a digital holographic imaging system using convolutional neural networks

Digital holographic imaging systems are promising three-dimensional imaging systems that acquire holograms via interference of a reference wave and an object wave. Using digital holography and the numerical diffraction theory, an image can be reconstructed at any distance from the hologram. However, accurate determination of the distance of the object from the hologram is required to focus the image. Various autofocusing algorithms have been studied. The conventional autofocusing algorithm creates the focused image by evaluating iteratively reconstructed images using focus metrics. Owing to the iterative image reconstruction process, the computational time is very long. In this paper, an autofocusing algorithm for a digital holographic imaging system using convolutional neural networks, similar to pattern recognition systems, is proposed. Using the proposed method, the distance of the object from the hologram is obtained more rapidly than using the conventional method.