Comparative Study of Recent Compressed Sensing Methodologies in Astronomical Images

  • Nidhin Prabhakar T.V.
  • Hemanth V.K.
  • Sachin Kumar S.
  • K. P. Soman
  • Arun Soman
Part of the Communications in Computer and Information Science book series (CCIS, volume 305)

Abstract

Compressed sensing(CS) which serves as an alternative to Nyquist sampling theory, is being used in many areas of applications. In this paper, we applied recent compressed sensing algorithm such as DALM, FISTA and Split-Bregman on astronomical images. In astronomy, physical prior information is very crucial for devising effective signal processing methods. We particularly point out that CS-based compression scheme is flexible enough to account for such information. We try to compare these algorithms using objective measures like PSNR, MSE et al. With these measures we intend to verify the image quality of reconstructed and original images.

Keywords

Compressed Sensing Image Quality Assessment Compressive Sampling Signal Processing Method Astronomical Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nidhin Prabhakar T.V.
    • 1
  • Hemanth V.K.
    • 1
  • Sachin Kumar S.
    • 1
  • K. P. Soman
    • 1
  • Arun Soman
    • 2
  1. 1.Centre for Excellence in Computational Engineering and NetworkingAmrita UniversityCoimbatoreIndia
  2. 2.Department of Information TechnologyRajagiri School of Engineering & TechnologyIndia

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