A Differentiable Wave Optics Model for End-to-End Computational Imaging System Optimization
Journal:
arXiv
Published Date:
Dec 13, 2024
Abstract
End-to-end optimization, which simultaneously optimizes optics and
algorithms, has emerged as a powerful data-driven method for computational
imaging system design. This method achieves joint optimization through
backpropagation by incorporating differentiable optics simulators to generate
measurements and algorithms to extract information from measurements. However,
due to high computational costs, it is challenging to model both aberration and
diffraction in light transport for end-to-end optimization of compound optics.
Therefore, most existing methods compromise physical accuracy by neglecting
wave optics effects or off-axis aberrations, which raises concerns about the
robustness of the resulting designs. In this paper, we propose a differentiable
optics simulator that efficiently models both aberration and diffraction for
compound optics. Using the simulator, we conduct end-to-end optimization on
scene reconstruction and classification. Experimental results demonstrate that
both lenses and algorithms adopt different configurations depending on whether
wave optics is modeled. We also show that systems optimized without wave optics
suffer from performance degradation when wave optics effects are introduced
during testing. These findings underscore the importance of accurate wave
optics modeling in optimizing imaging systems for robust, high-performance
applications.
