Modeling and analysis of a monocentric multi-scale optical system

Huang, Yunhan; Fu, Yuegang; Zhang, Guoyu; Liu, Zhiying

doi:10.1364/oe.406213

Cited by 11 publications

(2 citation statements)

References 13 publications

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“…This design not only solved the contradiction between wide FoV and high resolution but also provided a new design idea for computational imaging. A new analytical model of Galileo Monocentric Multi-Scale (GMMS) and Keplerian Monocentric Multi-Scale (KMMS) was proposed in [118], which is more accurate than the paraxial form. The model avoids the laborious analysis of different monocentric lens forms and maintains the key points of the Monocentric Multi-Scale (MMS) system.…”

Section: E Monocentric Panoramic Systemmentioning

confidence: 99%

Review on Panoramic Imaging and Its Applications in Scene Understanding

Gao¹,

Yang²,

Sheng³

et al. 2022

Preprint

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With the rapid development of high-speed communication and artificial intelligence technologies, human perception of real-world scenes is no longer limited to the use of small Field of View (FoV) and low-dimensional scene detection devices. Panoramic imaging emerges as the next generation of innovative intelligent instruments for environmental perception and measurement. However, while satisfying the need for large-FoV photographic imaging, panoramic imaging instruments are expected to have high resolution, no blind area, miniaturization, and multi-dimensional intelligent perception, and can be combined with artificial intelligence methods towards the next generation of intelligent instruments, enabling deeper understanding and more holistic perception of 360 • real-world surrounding environments. Fortunately, recent advances in freeform surfaces, thinplate optics, and metasurfaces provide innovative approaches to address human perception of the environment, offering promising ideas beyond conventional optical imaging. In this review, we begin with introducing the basic principles of panoramic imaging systems, and then describe the architectures, features, and functions of various panoramic imaging systems. Afterwards, we discuss in detail the broad application prospects and great design potential of freeform surfaces, thin-plate optics, and metasurfaces in panoramic imaging. We then provide a detailed analysis on how these techniques can help enhance the performance of panoramic imaging systems. We further offer a detailed analysis of applications of panoramic imaging in scene understanding for autonomous driving and robotics, spanning panoramic semantic image segmentation, panoramic depth estimation, panoramic visual localization, and so on. Finally, we cast a perspective on future potential and research directions for panoramic imaging instruments.

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Section: E Monocentric Panoramic Systemmentioning

confidence: 99%

Review on Panoramic Imaging and Its Applications in Scene Understanding

Gao¹,

Yang²,

Sheng³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…In existing implementations, fisheye and reflective panoramic lenses can provide a large FOV, but the optical system usually suffers from large aberrations and distortions [5] that degenerate the image quality, and the narrow aperture of the entrance pupil makes it difficult to improve the resolving power [6]. Spherical lenses with concentrically arranged fiber bundles or detector arrays [7,8] may result in a significant increase in volume and pose challenges for achieving long focal length. Camera arrays can offer a balance between spatial resolution and FOV, but this also comes at the cost of SWaP [9].…”

Section: Introductionmentioning

confidence: 99%

Coverage Path Planning with Adaptive Hyperbolic Grid for Step-Stare Imaging System

Zhao

2024

Drones

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Step-stare imaging systems are widely used in aerospace optical remote sensing. In order to achieve fast scanning of the target region, efficient coverage path planning (CPP) is a key challenge. However, traditional CPP methods are mostly designed for fixed cameras and disregard the irregular shape of the sensor’s projection caused by the step-stare rotational motion. To address this problem, this paper proposes an efficient, seamless CPP method with an adaptive hyperbolic grid. First, we convert the coverage problem in Euclidean space to a tiling problem in spherical space. A spherical approximate tiling method based on a zonal isosceles trapezoid is developed to construct a seamless hyperbolic grid. Then, we present a dual-caliper optimization algorithm to further compress the grid and improve the coverage efficiency. Finally, both boustrophedon and branch-and-bound approaches are utilized to generate rotation paths for different scanning scenarios. Experiments were conducted on a custom dataset consisting of 800 diverse geometric regions (including 2 geometry types and 40 samples for 10 groups). The proposed method demonstrates comparable performance of closed-form path length relative to that of a heuristic optimization method while significantly improving real-time capabilities by a minimum factor of 2464. Furthermore, in comparison to traditional rule-based methods, our approach has been shown to reduce the rotational path length by at least 27.29% and 16.71% in circle and convex polygon groups, respectively, indicating a significant improvement in planning efficiency.

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