21 February 2017 Method of computer-generated hologram compression and transmission using quantum back-propagation neural network
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Abstract
A method for computer-generated hologram (CGH) compression and transmission using a quantum back-propagation neural network (QBPNN) is proposed, with the Fresnel transform technique adopted for image reconstruction of the compressed and transmitted CGH. Experiments of simulation were conducted to compare the reconstructed images from CGHs processed using a QBPNN with those processed using a back-propagation neural network (BPNN) at the optimal learning coefficients. The experimental results show that the method using a QBPNN could produce reconstructed images with a better quality than those obtained using a BPNN despite the use of fewer learning iterations at the same compression ratio.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Mengjia Liu, Mengjia Liu, Guanglin Yang, Guanglin Yang, Haiyan Xie, Haiyan Xie, } "Method of computer-generated hologram compression and transmission using quantum back-propagation neural network," Optical Engineering 56(2), 023104 (21 February 2017). https://doi.org/10.1117/1.OE.56.2.023104 . Submission: Received: 11 October 2016; Accepted: 7 February 2017
Received: 11 October 2016; Accepted: 7 February 2017; Published: 21 February 2017
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