Dual Representation of Geometry for Ray Tracing Acceleration in Optical Systems with Freeform Surfaces

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Abstract

This paper explores the possibility of using dual geometry representation to improve the speed of ray tracing and ensure the robustness of light propagation simulations in complex optical systems containing free-form surfaces defined by high-order polynomials (up to order 34) or Jacobi polynomials. An analysis was carried out of traditional methods of representing this geometry both in the form of a triangular mesh and in the form of an analytical expression. The analysis demonstrated the disadvantages of traditional approaches, which consist in the insufficient accuracy of calculating the coordinates of the meeting point of the ray with a triangular mesh, as well as the instability of the results of searching for the hit point of tangent rays with the analytically defined surface when using existing calculation methods. As a result, it was proposed to use a dual representation of the geometry in the form of a rough approximation of the surface by a triangular mesh, which is subsequently used as an initial approximation to find the point where the ray hits the surface specified by the analytical expression. This solution made it possible to significantly speed up the convergence of analytical methods and increase their stability. Moreover, using the Intel® Embree library to quickly find the point of intersection of a ray with a coarse triangular mesh and a vector calculation model to refine the coordinates of the point of intersection of the ray with the geometry represented analytically allowed authors to develop and implement a ray tracing algorithm in an optical system containing surfaces with dual geometry representation. Experiments conducted using the developed and implemented algorithm show the significant acceleration of ray tracing while maintaining computational accuracy and high stability of results. The results were demonstrated by calculating the point and flare spread function for two lenses with free-form surfaces defined by Jacobi polynomials. In addition, for these two lenses, the image formed by an RGB-D object simulating a real scene was calculated.

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About the authors

D. D. Zhdanov

Saint Petersburg National Research University of Information Technologies, Mechanics and Optics

Author for correspondence.
Email: ddzhdanov@mail.ru
Russian Federation, Saint Petersburg

I. S. Potemin

Saint Petersburg National Research University of Information Technologies, Mechanics and Optics

Email: ipotemin@yandex.ru
Russian Federation, Saint Petersburg

A. D. Zhdanov

Saint Petersburg National Research University of Information Technologies, Mechanics and Optics

Email: andrew.gtx@gmail.com
Russian Federation, Saint Petersburg

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Supplementary files

Supplementary Files
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1. JATS XML
2. Fig. 1. Example of an augmented reality camera lens

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3. Fig. 2. Four-lens lens with aspherical surfaces represented by formula (2) - (a), five-lens lens with aspherical surfaces represented by formula (3) - (b)

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4. Fig. 3. PSF of a four-lens lens with aspherical surfaces represented by formula (2) - (a), FRT of a five-lens lens with aspherical surfaces represented by formula (3) - (b)

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5. Fig. 4. Deviations of the PSF from the standards for four-lens (a) and five-lens (b) lenses and three variants of triangular grid resolution: 24 × 54 (1), 240 × 540 (2), and 2400 × 5400 (3)

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6. Fig. 5. Optical system of the lens (upper figure) represented as a set of Embree scenes (lower figure)

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7. Fig. 6. Partitioning of the SSMD vector of eight single-precision real numbers into two vectors of four double-precision real numbers in the filter function

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8. Fig. 7. Determination of the initial meeting point of the beam with the aspherical surface, the upper part of the figure is the case of dual geometry representation, the lower part of the figure is the direct fitting by the algorithms [4] and [1]

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9. Fig. 8. Example of the algorithm for calculating the PSF

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10. Fig. 9. PSF of a four-lens lens (a) for three fields of view: 0° (1), 26° (2) and 37° (3) and PSF of a five-lens lens (b) for three fields of view: 0° (1), 19° (2) and 45° (3)

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11. Fig. 10. PSF of flare of a four-lens lens (a) for two fields of view: 48.5° (1) and 50° (2) and the PSF of the five-lens lens (b) for two fields of view: 48.5° (1), 50° (2)

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12. Fig. 11. RGB image (top) and depth map (bottom)

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13. Fig. 12. Images constructed with a four-lens lens (top) and a five-lens lens (bottom)

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