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基于色觉模糊视觉的水下高光谱成像。

Underwater hyperspectral imaging bioinspired by chromatic blur vision.

机构信息

Ocean College, Zhejiang University, Zhoushan 316021, People's Republic of China.

Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province, Zhejiang University, Zhoushan 316021, People's Republic of China.

出版信息

Bioinspir Biomim. 2022 Dec 15;18(1). doi: 10.1088/1748-3190/aca7a8.

Abstract

In the underwater environment, conventional hyperspectral imagers for imaging target scenes usually require stable carrying platforms for completing push sweep or complex optical components for beam splitting in long gaze imaging, which limits the system's efficiency. In this paper, we put forward a novel underwater hyperspectral imaging (UHI) system inspired by the visual features of typical cephalopods. We designed a visual bionic lens which enlarged the chromatic blur effect to further ensure that the system obtained blur images with high discrimination of different bands. Then, chromatic blur datasets were collected underwater to complete network training for hyperspectral image reconstruction. Based on the trained model, our system only required three frames of chromatic blur images as input to effectively reconstruct spectral images of 30 bands in the working light range from 430 nm to 720 nm. The results showed that the proposed hyperspectral imaging system exhibited good spectral imaging potential. Moreover, compared with the traditional gaze imaging, when obtaining similar hyperspectral images, the data sampling rate in the proposed system was reduced by 90%, and the exposure time of required images was only about 2.1 ms, reduced by 99.98%, which can greatly expand its practical application range. This experimental study illustrates the potential of chromatic blur vision for UHI, which can provide rapid response in the recognition task of some underwater dynamic scenarios.

摘要

在水下环境中,用于对目标场景成像的传统的高光谱成像仪通常需要稳定的承载平台来完成推扫,或者需要复杂的光学元件来进行长凝视成像中的光束分光,这限制了系统的效率。在本文中,我们受到典型头足类动物视觉特征的启发,提出了一种新颖的水下高光谱成像(UHI)系统。我们设计了一种视觉仿生透镜,放大了色模糊效果,以进一步确保系统获得具有高的不同波段分辨力的模糊图像。然后,在水下收集色模糊数据集,以完成用于高光谱图像重建的网络训练。基于训练好的模型,我们的系统仅需要三帧色模糊图像作为输入,就可以有效地重建工作光范围内从 430nm 到 720nm 的 30 个波段的光谱图像。结果表明,所提出的高光谱成像系统具有良好的光谱成像潜力。此外,与传统凝视成像相比,在获得类似的高光谱图像时,所提出系统的数据采样率降低了 90%,所需图像的曝光时间仅约为 2.1ms,降低了 99.98%,这可以极大地扩展其实际应用范围。这项实验研究说明了色模糊视觉在 UHI 中的应用潜力,它可以在一些水下动态场景的识别任务中提供快速响应。

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