Abstract—This paper presents a new approach for imaged noising based on compressed sensing. In this method, an unknown noisy image of interest is observed (sensed) through a limited number linear functional in random projection, the noriginal image is reconstructed using the observation vector and the existed recovery algorithms such as L1_minimization. Simulation results inform this method is an efficient method for image denoising.
Index Terms—Noise reduction, image processing, imaged noising, compressed sensing.
The authors are with the Electrical Engineering Department, Amirkabir University of Technology, Hafez Ave., Tehran 15914, Iran (e-mails: amintavakoli61@gmail.com, pourmohammad@aut.ac.ir, tel.: +98 2164543392, fax: +98 21 66406469).
Cite: Amin Tavakoli and Ali Pourmohammad, "Image Denoising Based on Compressed Sensing," International Journal of Computer Theory and Engineering vol. 4, no. 2, pp. 266-269, 2012.
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