Compressed sensing with cyclic-S Hadamard matrix for terahertz imaging applications


Ermeydan E. , Cankaya I.

6th International Eurasian Conference on Mathematical Sciences and Applications, IECMSA 2017, Budapest, Hungary, 15 - 18 August 2017, vol.1926 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 1926
  • Doi Number: 10.1063/1.5020489
  • City: Budapest
  • Country: Hungary

Abstract

© 2018 Author(s).Compressed Sensing (CS) with Cyclic-S Hadamard matrix is proposed for single pixel imaging applications in this study. In single pixel imaging scheme, N = r · c samples should be taken for r×c pixel image where · denotes multiplication. CS is a popular technique claiming that the sparse signals can be reconstructed with samples under Nyquist rate. Therefore to solve the slow data acquisition problem in Terahertz (THz) single pixel imaging, CS is a good candidate. However, changing mask for each measurement is a challenging problem since there is no commercial Spatial Light Modulators (SLM) for THz band yet, therefore circular masks are suggested so that for each measurement one or two column shifting will be enough to change the mask. The CS masks are designed using cyclic-S matrices based on Hadamard transform for 9 × 7 and 15 × 17 pixel images within the framework of this study. The %50 compressed images are reconstructed using total variation based TVAL3 algorithm. Matlab simulations demonstrates that cyclic-S matrices can be used for single pixel imaging based on CS. The circular masks have the advantage to reduce the mechanical SLMs to a single sliding strip, whereas the CS helps to reduce acquisition time and energy since it allows to reconstruct the image from fewer samples.