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采用快照窄带成像方法的微型4D成像传感器。

Micro 4D Imaging Sensor Using Snapshot Narrowband Imaging Method.

作者信息

Jiang Wei, Yi Dingrong, Huang Caihong, Yu Qing, Kong Linghua

机构信息

College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China.

School of Mechanical and Automotive Engineering, Fujian University of Technology, Fuzhou 350118, China.

出版信息

Micromachines (Basel). 2023 Aug 29;14(9):1689. doi: 10.3390/mi14091689.

Abstract

The spectral and depth (SAD) imaging method plays an important role in the field of computer vision. However, accurate depth estimation and spectral image capture from a single image without increasing the volume of the imaging sensor is still an unresolved problem. Our research finds that a snapshot narrow band imaging (SNBI) method can discern wavelength-dependent spectral aberration and simultaneously capture spectral-aberration defocused images for quantitative depth estimation. First, a micro 4D imaging (M4DI) sensor is proposed by integrating a mono-chromatic imaging sensor with a miniaturized narrow-band microarrayed spectral filter mosaic. The appearance and volume of the M4DI sensor are the same as the integrated mono-chromatic imaging sensor. A simple remapping algorithm was developed to separate the raw image into four narrow spectral band images. Then, a depth estimation algorithm is developed to generate 3D data with a dense depth map at every exposure of the M4DI sensor. Compared with existing SAD imaging method, the M4DI sensor has the advantages of simple implementation, low computational burden, and low cost. A proof-of-principle M4DI sensor was applied to sense the depth of objects and to track a tiny targets trajectory. The relative error in the three-dimensional positioning is less than 7% for objects within 1.1 to 2.8 m.

摘要

光谱与深度(SAD)成像方法在计算机视觉领域发挥着重要作用。然而,在不增加成像传感器体积的情况下,从单幅图像进行精确的深度估计和光谱图像捕捉仍是一个未解决的问题。我们的研究发现,快照窄带成像(SNBI)方法能够辨别波长相关的光谱像差,并同时捕捉光谱像差散焦图像以进行定量深度估计。首先,通过将单色成像传感器与小型化窄带微阵列光谱滤光片镶嵌体集成,提出了一种微型4D成像(M4DI)传感器。M4DI传感器的外观和体积与集成的单色成像传感器相同。开发了一种简单的重映射算法,将原始图像分离为四个窄光谱带图像。然后,开发了一种深度估计算法,以在M4DI传感器的每次曝光时生成具有密集深度图的3D数据。与现有的SAD成像方法相比,M4DI传感器具有实现简单、计算负担低和成本低的优点。一个原理验证的M4DI传感器被应用于感知物体的深度并跟踪微小目标的轨迹。对于距离在1.1至2.8米内的物体,三维定位的相对误差小于7%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/618c/10536809/e5718d1b8b29/micromachines-14-01689-g001.jpg

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