Approaching direct optimization of as-built lens performance

McGuire, James P.; Kuper, Thomas G.

doi:10.1117/12.930568

Cited by 5 publications

(2 citation statements)

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“…During the design stage, as usual, the design is fully optimized to minimize spot size of each ray on the image plane. The method of optimizing the lens design can be found in many references [10][11][12][13]. Once the design has been optimized to achieve the desired optical performance which include the Modulation Transfer Function (MTF), distortion and field of view etc, the next step is to run Monte-Carlo tolerance simulation.…”

Section: Current Approachmentioning

confidence: 99%

Self-image correction for low-cost imaging optic

Wang

Whitaker

2023

ETN

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With the advent of computing power and higher resolution CMOS sensor, imaging camera for mobile phone application has become very common in consumer portable product such as mobile phone, tablet or even wearable devices and head mount devices . Higher resolution image sensor, on the other hand, will suffer chromatic aberration (CA) where the colour channel appears shifted. Better lens design with more lens elements may be required. However, this will add more cost and manufacturing challenges. Many studies and methods have been proposed for CA correction through post image processing and those methods required calibration or post image process before correction factor can be applied. In this paper, we propose a new algorithm that will pre-defined the CA correction factor through lens design simulation.

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Section: Current Approachmentioning

confidence: 99%

Self-image correction for low-cost imaging optic

Wang

Whitaker

2023

ETN

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“…With high-order aspherical surfaces or more optimization variables implemented in modern lens designs processes, the optimization process is becoming further sophisticated with new techniques, such as integrating manufacturing tolerances into optimization in order to achieve minimal performance degradation with as-built lenses [25,26] or incorporating computational photography steps into the lens design stage [27][28][29]. In general, optimization algorithms applied to optical systems can be divided into classical gradientbased optimization algorithms based on the least-squares (LS) method [30][31][32][33][34][35] and modern optimization algorithms based on the analogy with natural evolution.…”

Section: Overview Of Optical Imaging System Designmentioning

confidence: 99%

A Surrogate Model Based Multi-Objective Optimization Method for Optical Imaging System

et al. 2022

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An optimization model for the optical imaging system was established in this paper. It combined the modern design of experiments (DOE) method known as Latin hypercube sampling (LHS), Kriging surrogate model training, and the multi-objective optimization algorithm NSGA-III into the optimization of a triplet optical system. Compared with the methods that rely mainly on optical system simulation, this surrogate model-based multi-objective optimization method can achieve a high-accuracy result with significantly improved optimization efficiency. Using this model, case studies were carried out for two-objective optimizations of a Cooke triplet optical system. The results showed that the weighted geometric spot diagram and the maximum field curvature were reduced 5.32% and 11.59%, respectively, in the first case. In the second case, where the initial parameters were already optimized by Code-V, this model further reduced the weighted geometric spot diagram and the maximum field curvature by another 3.53% and 4.33%, respectively. The imaging quality in both cases was considerably improved compared with the initial design, indicating that the model is suitable for the optimal design of an optical system.

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Starting geometry creation and design method for freeform optics

2018

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We describe a method for designing freeform optics based on the aberration theory of freeform surfaces that guides the development of a taxonomy of starting-point geometries with an emphasis on manufacturability. An unconventional approach to the optimization of these starting designs wherein the rotationally invariant 3rd-order aberrations are left uncorrected prior to unobscuring the system is shown to be effective. The optimal starting-point geometry is created for an F/3, 200 mm aperture-class three-mirror imager and is fully optimized using a novel step-by-step method over a 4 × 4 degree field-of-view to exemplify the design method. We then optimize an alternative starting-point geometry that is common in the literature but was quantified here as a sub-optimal candidate for optimization with freeform surfaces. A comparison of the optimized geometries shows the performance of the optimal geometry is at least 16× better, which underscores the importance of the geometry when designing freeform optics.

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Approaching direct optimization of as-built lens performance

Cited by 5 publications

References 0 publications

Self-image correction for low-cost imaging optic

Self-image correction for low-cost imaging optic

A Surrogate Model Based Multi-Objective Optimization Method for Optical Imaging System

Starting geometry creation and design method for freeform optics

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