Successive Optimization of Optics and Post-Processing With Differentiable Coherent PSF Operator and Field Information

IF 4.2 2区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Zheng Ren;Jingwen Zhou;Wenguan Zhang;Jiapu Yan;Bingkun Chen;Huajun Feng;Shiqi Chen
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引用次数: 0

Abstract

Recently, the joint design of optical systems and downstream algorithms is showing significant potential. However, existing rays-described methods are limited to optimizing geometric degradation, making it difficult to fully represent the optical characteristics of complex, miniaturized lenses constrained by wavefront aberration or diffraction effects. In this work, we introduce a precise optical simulation model, and every operation in pipeline is differentiable. This model employs a novel initial value strategy to enhance the reliability of intersection calculation on high aspherics. Moreover, it utilizes a differential operator to reduce memory consumption during coherent point spread function calculations. To efficiently address various degradation, we design a joint optimization procedure that leverages field information. Guided by a general restoration network, the proposed method not only enhances the image quality, but also successively improves the optical performance across multiple lenses that are already in professional level. This joint optimization pipeline offers innovative insights into the practical design of sophisticated optical systems and post-processing algorithms.
相干PSF算子和场信息可微的光学连续优化及后处理
近年来,光学系统和下游算法的联合设计显示出巨大的潜力。然而,现有的射线描述方法仅限于优化几何退化,因此难以完全表示受波前像差或衍射效应约束的复杂、小型化透镜的光学特性。在本文中,我们引入了一个精确的光学仿真模型,并且管道中的每个操作都是可微的。该模型采用了一种新颖的初值策略,提高了高非球面相交计算的可靠性。此外,它还利用微分算子来减少相干点扩展函数计算时的内存消耗。为了有效地解决各种退化问题,我们设计了一个利用现场信息的联合优化程序。在一般恢复网络的指导下,该方法不仅提高了图像质量,而且还不断提高了已经达到专业水平的多镜头光学性能。这种联合优化管道为复杂光学系统和后处理算法的实际设计提供了创新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Computational Imaging
IEEE Transactions on Computational Imaging Mathematics-Computational Mathematics
CiteScore
8.20
自引率
7.40%
发文量
59
期刊介绍: The IEEE Transactions on Computational Imaging will publish articles where computation plays an integral role in the image formation process. Papers will cover all areas of computational imaging ranging from fundamental theoretical methods to the latest innovative computational imaging system designs. Topics of interest will include advanced algorithms and mathematical techniques, model-based data inversion, methods for image and signal recovery from sparse and incomplete data, techniques for non-traditional sensing of image data, methods for dynamic information acquisition and extraction from imaging sensors, software and hardware for efficient computation in imaging systems, and highly novel imaging system design.
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