Enhancing All-in-Focus Imaging with Opto-Electronic Computational Camera using DE-ED Paradigm

Abstract

A novel approach called DE-ED (Diffractive Encoding-Electronic Decoding) for rapid all-in-focus capturing is presented in this paper. The paradigm combines the strengths of diffractive networks (DON) for encoding and electronic-based networks (ENN) for decoding, resulting in a robust computational imaging framework driven by advanced deep learning techniques. By leveraging the collaboration between diffractive layers and electronic layers, our model achieves remarkable enhancements in the ability to generalize and fit data. This means that the model can effectively capture and process complex visual information, resulting in superior image quality and enhanced performance.