Title :
Statistical mechanics approach to sparse noise denoising
Author :
Vehkapera, Mikko ; Kabashima, Yoshiyuki ; Chatterjee, Saptarshi
Author_Institution :
ACCESS Linnaeus Centre, KTH R. Inst. of Technol., Stockholm, Sweden
Abstract :
Reconstruction fidelity of sparse signals contaminated by sparse noise is considered. Statistical mechanics inspired tools are used to show that the ℓ1-norm based convex optimization algorithm exhibits a phase transition between the possibility of perfect and imperfect reconstruction. Conditions characterizing this threshold are derived and the mean square error of the estimate is obtained for the case when perfect reconstruction is not possible. Detailed calculations are provided to expose the mathematical tools to a wide audience.
Keywords :
compressed sensing; image denoising; image reconstruction; mean square error methods; optimisation; statistical mechanics; convex optimization algorithm; mean square error; phase transition; reconstruction fidelity; sparse noise denoising; sparse signals; statistical mechanics; Abstracts; Multiaccess communication; Radio access networks; replica method; sparse signals and noise; statistical mechanical analysis;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
Conference_Location :
Marrakech
