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利用具有偏移像素孔径技术的 CMOS 图像传感器进行深度提取的视差信息分析。

Analysis of Disparity Information for Depth Extraction Using CMOS Image Sensor with Offset Pixel Aperture Technique.

机构信息

School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea.

Center for Integrated Smart Sensors, KAIST, Daejeon 34141, Korea.

出版信息

Sensors (Basel). 2019 Jan 24;19(3):472. doi: 10.3390/s19030472.

DOI:10.3390/s19030472
PMID:30682783
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6387063/
Abstract

A complementary metal oxide semiconductor (CMOS) image sensor (CIS), using offset pixel aperture (OPA) technique, was designed and fabricated using the 0.11-µm CIS process. In conventional cameras, an aperture is located on the camera lens. However, in a CIS camera using OPA technique, apertures are integrated as left-offset pixel apertures (LOPAs) and right-offset pixel apertures (ROPAs). A color pattern is built, comprising LOPA, blue, red, green, and ROPA pixels. The disparity information can be acquired from the LOPA and ROPA channels. Both disparity information and two-dimensional (2D) color information can be simultaneously acquired from the LOPA, blue, red, green, and ROPA channels. A geometric model of the OPA technique is constructed to estimate the disparity of the image, and the measurement results are compared with the estimated results. Depth extraction is thus achieved by a single CIS using the OPA technique, which can be easily adapted to commercial CIS cameras.

摘要

互补金属氧化物半导体(CMOS)图像传感器(CIS)采用偏移像素孔径(OPA)技术,使用 0.11-µm CIS 工艺进行设计和制造。在传统相机中,孔径位于相机镜头上。然而,在使用 OPA 技术的 CIS 相机中,孔径被集成作为左偏移像素孔径(LOPA)和右偏移像素孔径(ROPA)。构建了一个包含 LOPA、蓝色、红色、绿色和 ROPA 像素的彩色图案。视差信息可以从 LOPA 和 ROPA 通道获取。可以从 LOPA、蓝色、红色、绿色和 ROPA 通道同时获取视差信息和二维(2D)彩色信息。构建了 OPA 技术的几何模型来估计图像的视差,并且将测量结果与估计结果进行了比较。通过使用 OPA 技术的单个 CIS 可以实现深度提取,这可以很容易地适应商业 CIS 相机。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/a6c5359fdc89/sensors-19-00472-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/f8bd5349ba8b/sensors-19-00472-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/64b34f9d9c2b/sensors-19-00472-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/69578d7c524c/sensors-19-00472-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/941be0b0d8dc/sensors-19-00472-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/966f2e10a999/sensors-19-00472-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/0ff1e47a69e1/sensors-19-00472-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/a656224fb5d3/sensors-19-00472-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/a6c5359fdc89/sensors-19-00472-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/f8bd5349ba8b/sensors-19-00472-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/64b34f9d9c2b/sensors-19-00472-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/69578d7c524c/sensors-19-00472-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/941be0b0d8dc/sensors-19-00472-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/966f2e10a999/sensors-19-00472-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/0ff1e47a69e1/sensors-19-00472-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/a656224fb5d3/sensors-19-00472-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d244/6387063/a6c5359fdc89/sensors-19-00472-g008.jpg

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3
Depth map generation using a single image sensor with phase masks.使用带有相位掩膜的单图像传感器生成深度图。
Opt Express. 2016 Jun 13;24(12):12868-78. doi: 10.1364/OE.24.012868.
4
A Self-Assessment Stereo Capture Model Applicable to the Internet of Things.一种适用于物联网的自评估立体捕捉模型。
Sensors (Basel). 2015 Aug 21;15(8):20925-44. doi: 10.3390/s150820925.
5
Sensors for 3D Imaging: Metric Evaluation and Calibration of a CCD/CMOS Time-of-Flight Camera.3D 成像传感器:CCD/CMOS 飞行时间相机的度量评估和校准。
Sensors (Basel). 2009;9(12):10080-96. doi: 10.3390/s91210080. Epub 2009 Dec 11.