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Proceedings Paper

Pixel arrangement design of retina-like sensor based on forward motion imaging visual task
Author(s): Fan Wang; Fengmei Cao; Tingzhu Bai; Zhihu Luo; Yulu Su
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Paper Abstract

Retina-like sensor is a kind of anthropomorphic visual sensor, which mimic the distribution of photoreceptors in the human retina. They are applied in fields of machine vision and target tracking. However, there are few reports on retina-like sensor used for forward-motion imaging. During forward-motion imaging, as the objects being imaged move along the optical axis direction during the integration time, image quality becomes worse towards the border of the image. In order to get clearer image, retina-like sensor are trying to be designed based on the feature of forward-motion imaging. In this paper, firstly, the degraded law of rectilinear sensor used for forward-motion imaging is analyzed, the retina-like sensor model based on the feature of forward-motion imaging are proposed. Secondly, the output image of retina-like sensor and rectilinear sensor used during the forward-motion imaging for different scenes at different degeneration degrees are simulated, respectively. Thirdly, the simulated images of both two sensors are assessed by four different image quality assessment methods including visual information fidelity (VIF), complex wavelet structural similarity index (CW-SSIM), Gabor filtered image contrast similarity (GFCS) and peak signal to noise ratio (PSNR), besides, the data amount of two sensors are compared. Four image quality assessments all demonstrate that image quality of retina-like sensor based on the feature of forward motion imaging is superior to that of rectilinear sensor.

Paper Details

Date Published: 24 November 2014
PDF: 11 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930107 (24 November 2014); doi: 10.1117/12.2065109
Show Author Affiliations
Fan Wang, Beijing Institute of Technology (China)
Fengmei Cao, Beijing Institute of Technology (China)
Tingzhu Bai, Beijing Institute of Technology (China)
Zhihu Luo, Beijing Institute of Technology (China)
Yulu Su, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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