Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79742
Title: Information retrieval based on single-pixel optical imaging with quick-response code
Authors: Xiao, Y 
Chen, W 
Keywords: QR code
Ghost imaging
Gerchberg-Saxton-like algorithm
Issue Date: 2018
Publisher: SPIE-International Society for Optical Engineering
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2018, v. 10615, UNSP 106153H How to cite?
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
Abstract: Quick-response (QR) code technique is combined with ghost imaging (GI) to recover original information with high quality. An image is first transformed into a QR code. Then the QR code is treated as an input image in the input plane of a ghost imaging setup. After measurements, traditional correlation algorithm of ghost imaging is utilized to reconstruct an image (QR code form) with low quality. With this low-quality image as an initial guess, a Gerchberg-Saxton-like algorithm is used to improve its contrast, which is actually a post processing. Taking advantage of high error correction capability of QR code, original information can be recovered with high quality. Compared to the previous method, our method can obtain a high-quality image with comparatively fewer measurements, which means that the time-consuming postprocessing procedure can be avoided to some extent. In addition, for conventional ghost imaging, the larger the image size is, the more measurements are needed. However, for our method, images with different sizes can be converted into QR code with the same small size by using a QR generator. Hence, for the larger-size images, the time required to recover original information with high quality will be dramatically reduced. Our method makes it easy to recover a color image in a ghost imaging setup, because it is not necessary to divide the color image into three channels and respectively recover them.
Description: 9th International Conference on Graphic and Image Processing (ICGIP), Ocean University China, Academic Exchange Center, Qingdao, People's Republic of China, Oct 14-16, 2017
URI: http://hdl.handle.net/10397/79742
ISBN: 978-1-5106-1742-1
ISSN: 0277-786X
EISSN: 1996-756X
DOI: 10.1117/12.2302607
Appears in Collections:Conference Paper

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