Veeranna, Suresh Kaggere
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Image reconstruction through compressive sampling matching pursuit and curvelet transform Seetharamaswamy, Shashi Kiran; Veeranna, Suresh Kaggere
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6277-6284

Abstract

An interesting area of research is image reconstruction, which uses algorithms and techniques to transform a degraded image into a good one. The quality of the reconstructed image plays a vital role in the field of image processing. Compressive Sampling is an innovative and rapidly growing method for reconstructing signals. It is extensively used in image reconstruction. The literature uses a variety of matching pursuits for image reconstruction. In this paper, we propose a modified method named compressive sampling matching pursuit (CoSaMP) for image reconstruction that promises to sample sparse signals from far fewer observations than the signal’s dimension. The main advantage of CoSaMP is that it has an excellent theoretical guarantee for convergence. The proposed technique combines CoSaMP with curvelet transform for better reconstruction of image. Experiments are carried out to evaluate the proposed technique on different test images. The results indicate that qualitative and quantitative performance is better compared to existing methods.