DocumentCode :
170426
Title :
Image storage, retrieval and compression in entangled quantum systems
Author :
Haisheng Li ; Qingxin Zhu ; Rigui Zhou ; Yonghua Pu ; Lan Song
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2014
fDate :
16-18 May 2014
Firstpage :
237
Lastpage :
241
Abstract :
A novel method is proposed in this paper to store and retrieve images in entangled quantum systems, i.e., we employ a 2-qubit (or 3-qubit) entangled quantum state to represent the colors of 3 pixels (or 5 pixels) of color or gray images, and design quantum circuits to store images in entangled quantum systems, in addition, illustrate how to retrieve images stored in entangled quantum systems and analyze that the number of measurement is needed at most to retrieve a correct entangled quantum state. Simulation results on the Lena image shows compression ratio is 5.7 when PSNR is 32.8DB by Fourier transform while compression ratio of 2-qubit entangled coding (i.e., 2-qubit entangled quantum states represent image colors) is 12 without losing any information of the image. Due to take advantage of the superposition and entanglement properties of quantum states, our method improves the ability of image compression.
Keywords :
data compression; image coding; image colour analysis; image representation; image retrieval; quantum computing; quantum entanglement; 2-qubit entangled coding; 2-qubit entangled quantum states; Fourier transform; Lena image compression ratio; PSNR; entangled quantum systems; entanglement properties; gray images; image color representation; image retrieval; image storage; quantum circuits; Color; Image coding; Image color analysis; Image storage; Logic gates; Quantum computing; Quantum entanglement; Image compression; Image storage and retrieval; Quantum entanglement; Quantum image processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Progress in Informatics and Computing (PIC), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-2033-4
Type :
conf
DOI :
10.1109/PIC.2014.6972332
Filename :
6972332
Link To Document :
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