Earticle

초록

영어

Compressed sensing is a new signal sampling theory that fully makes use of signal’s sparsity or compressibility. The theory shows that, the acquisition of a small amount of the sparse or compressible signal value can be used for exact signal reconstruction. Based on the study and summarization of the existing reconstruction algorithms, this paper proposes a novel blocking variable step size forward-backward pursuit (BVSSFBP). This paper proposed variable step size forward-backward pursuit algorithm by introducing the concept of sparse phase and variable step size to deal with different situations. The algorithm also divides two-dimensional image into blocks, in order to reduce the scale of observation matrix during single processing, reduce the single processing speed and the overall running time. Experimental results show BVSSFBP algorithm can obtain better reconstructed image quality.

목차

Abstract
 1. Introduction
 2. Compressed Sensing and Reconstruction Algorithm
 3. VSFBP Algorithm
 4. BVSSFBP Algorithm
 5. Experiments and Analysis
  5.1 The Selection of Block Size
  5.2 The Selection of Sampling Rate
  5.3 Equalization Operation
 6. Conclusion
 References

키워드

저자

• AiliWang [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Mingji Yang [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Xue Gao [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Yuji Iwahori [ Dept. of Computer Science, Chubu University, Japan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605