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Offset Aperture: A Passive Single-Lens Camera for Depth Sensing
- Source :
- IEEE Transactions on Circuits and Systems for Video Technology. 29:1380-1393
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Numerous camera sensors have been recently proposed to estimate the depth of objects in the scene. However, many of these sensors either require multiple imaging elements or an active illuminant. In this paper, we propose a new depth camera, termed offset aperture (OA) camera, which provides depth of the scene with a single shot without an active illuminant. The camera is based on a 4-color sensor that senses the infrared (IR) signal along with the visible RGB signals. Separate OAs are used for IR and RGB images. A depth-dependent disparity is generated between the IR and RGB images. There is no disparity across the R, G, and B channel images, which allows the RGB image to be well-aligned. Numerous techniques are used in this work to observe good-quality depth maps and images. Leakage compensation has been proposed to remove crosstalk between the IR and RGB images. A comparison with another 4-color sensor called Dual Aperture camera shows that OA camera provides 88% improvement in depth sensitivity and 45% improvement in color quality, on average. The proposed OA camera can be used for numerous applications including occlusion handling in stereo, selective focus, and night vision. The advantages of the proposed OA camera include competitive image quality, capability of depth extraction, well-aligned RGB images, and small footprint of the camera, which make OA camera a suitable candidate for mobile applications.
- Subjects :
- Color quality
Offset (computer science)
Infrared
Aperture
Image quality
Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Standard illuminant
02 engineering and technology
0202 electrical engineering, electronic engineering, information engineering
Media Technology
RGB color model
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
Electrical and Electronic Engineering
Image sensor
business
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- ISSN :
- 15582205 and 10518215
- Volume :
- 29
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Circuits and Systems for Video Technology
- Accession number :
- edsair.doi...........9c587b6fc0a77b50792a967aea063b28
- Full Text :
- https://doi.org/10.1109/tcsvt.2018.2840053