Improvement in design of panoramic annular lens using cemented lenses

Niu, Shuang; Bai, Jian; Hou, Xiyun; Yang, Guoguang

doi:10.1117/12.755572

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Due to the catadioptric structure of the PAL head, a PAL can achieve 360 • panoramic imaging, where incident rays of 360 • FoV are collected and bent to a beam with small angle. To correct aberrations in different FoVs, complex relay lens groups are applied so that traditional PAL systems normally consist of more than 8 lenses [15]- [17]. Simplifying the number of lenses is becoming a hot research topic.…”

Section: Introductionmentioning

confidence: 99%

Annular Computational Imaging: Capture Clear Panoramic Images through Simple Lens

Jiang¹,

Sheng²,

Sun³

et al. 2022

Preprint

View full text Add to dashboard Cite

Panoramic Annular Lens (PAL), composed of few lenses, has great potential in panoramic surrounding sensing tasks for mobile and wearable devices because of its tiny size and large Field of View (FoV). However, the image quality of tiny-volume PAL confines to optical limit due to the lack of lenses for aberration correction. In this paper, we propose an Annular Computational Imaging (ACI) framework to break the optical limit of light-weight PAL design. To facilitate learning-based image restoration, we introduce a wave-based simulation pipeline for panoramic imaging and tackle the synthetic-to-real gap through multiple data distributions. The proposed pipeline can be easily adapted to any PAL with design parameters and is suitable for loose-tolerance designs. Furthermore, we design the Physics Informed Image Restoration Network (PI 2 RNet), considering the physical priors of panoramic imaging and physics-informed learning. At the dataset level, we create the DIVPano dataset and the extensive experiments on it illustrate that our proposed network sets the new state of the art in the panoramic image restoration under spatially-variant degradation. In addition, the evaluation of the proposed ACI on a simple PAL with only 3 spherical lenses reveals the delicate balance between high-quality panoramic imaging and compact design. To the best of our knowledge, we are the first to explore Computational Imaging (CI) in PAL. Code and datasets will be made publicly available at https://github.com/zju-jiangqi/ACI-PI2RNet.

show abstract

Section: Introductionmentioning

confidence: 99%