ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2014, Vol. 51 ›› Issue (9): 2070-2080.doi: 10.7544/issn1000-1239.2014.20130304

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Binary Pure Phase Encoding Compressive Imaging in Frequency Domain

Zhang Cheng1, Zhang Fen1,2, Shen Chuan1, Zhang Quanbing1, Wei Sui1, Wang Yue1   

  1. 1(Key Laboratory of Intelligent Computing & Signal Processing (Anhui University), Ministry of Education, Hefei 230039);2(Key Laboratory of Modern Imaging and Displaying Technology of Anhui Province, Hefei 230039)
  • Online:2014-09-01

Abstract: Super resolution (SR) is considered as one of the “holy grails” of optical imaging and image processing. The introduction of compressive sensing theory presents a novel super-resolution reconstruction method from a single low-resolution image, which can avoid the requirements for the multiple sub-pixel images of traditional superresolution method. Analyzing the requirements of the similarities and differences between compressed sensing measurement matrices and optical imaging systems, a binary phase encoding compressive imaging method based on the 4-f optical architecture is presented, with the phase in the frequency domain randomly modulated, which can achieve super-resolution reconstruction from single low-resolution measurement images obtained with single exposure conditions, no other additional information collected. Binary phase mask is much easier to implement than random phase mask with uniform distribution, which is a more viable scheme for physical realization of compressive imaging. Simulation experiments demonstrate that the proposed method can effectively capture compressive measurements and implement super-resolution reconstruction in a single shot condition. Furthermore, another experiments show that this method is also more applicable to large-scale image reconstruction compared with random demodulation (RD) proposed by Romberg in the reconstruction time, and more practical in the sampling scheme than RecPC method proposed by Yin.

Key words: compressive imaging, image super-resolution, random phase encoding, binary phase encoding, 4-f optical architecture