Motion deblurring based on compressed sensing

In this paper we propose a motion deblurring method based on compressed sensing (CS) since motion deblurring is inherently an underdetermined problem as signal reconstruction of CS. Firstly, we build two degradation models caused by camera motion with and without random noise. Secondly, the corresponding two motion deblurring models are modelled via CS recovery algorithm. Finally, we give the detailed steps to validate the performance of the solution according to the incoherence, which may be used for other similar deterministic systems. The experimental results show that the proposed method can achieve the effective image and the boundary information from the blur image with and without random noise. © 2013 by CESER Publications.