The research on binocular stereo video imaging and display system based on low-light CMOS

Ruobing Xie; Li Li; Weiqi Jin; Hong Guo

doi:10.1117/12.2199808

8 October 2015 The research on binocular stereo video imaging and display system based on low-light CMOS

Ruobing Xie, Li Li, Weiqi Jin, Hong Guo

Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 967522 (2015) https://doi.org/10.1117/12.2199808
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

Abstract

It is prevalent for the low-light night-vision helmet to equip the binocular viewer with image intensifiers. Such equipment can not only acquire night vision ability, but also obtain the sense of stereo vision to achieve better perception and understanding of the visual field. However, since the image intensifier is for direct-observation, it is difficult to apply the modern image processing technology. As a result, developing digital video technology in night vision is of great significance. In this paper, we design a low-light night-vision helmet with digital imaging device. It consists of three parts: a set of two low-illumination CMOS cameras, a binocular OLED micro display and an image processing PCB. Stereopsis is achieved through the binocular OLED micro display. We choose Speed-Up Robust Feature (SURF) algorithm for image registration. Based on the image matching information and the cameras’ calibration parameters, disparity can be calculated in real-time. We then elaborately derive the constraints of binocular stereo display. The sense of stereo vision can be obtained by dynamically adjusting the content of the binocular OLED micro display. There is sufficient space for function extensions in our system. The performance of this low-light night-vision helmet can be further enhanced in combination with The HDR technology and image fusion technology, etc.

Citation Download Citation

Ruobing Xie, Li Li, Weiqi Jin, and Hong Guo "The research on binocular stereo video imaging and display system based on low-light CMOS", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 967522 (8 October 2015); https://doi.org/10.1117/12.2199808

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