Image Reconstruction Using Autofocus in Single-Lens System

Fast autofocusing based on pixel difference with the Tanimoto coefficient between images

Focusing objects accurately over short time scales is an essential and nontrivial task for a variety of microscopy applications. In this Letter, an autofocusing algorithm using pixel difference with the Tanimoto coefficient (PDTC) is described to predict the focus. Our method can robustly distinguish differences in clarity among datasets. The generated auto-focusing curves have extremely high sensitivity. A dataset of a defocused stack acquired by an Olympus microscope demonstrates the feasibility of our technique. This work can be applied in full-color microscopic imaging systems and is also valid for single-color imaging.

Random motion blur for optical image encryption

We present a compact optical encryption scheme by using a continuous-random-motion blurring model in an optical imaging system. Image encryption is performed by additive motion blur effects with continuous and random shifts of a camera. Real-time random phase modulation can be achieved without the use of random phase mask. Storage of the key is more convenient, which only requires parameters of motion. In addition, modulation characteristics are different from the traditional encryption schemes. On the premise of high security, modulation space is broadened, and flexibility of encryption is further improved. Simulations and experiments verify the validity of the motion blur-based crypto-system and demonstrate its security under several attacks. This novel method will be significant for the practical applications in the field of optical information security.