Efficient hardware implementation of the Richardson-Lucy Algorithm for restoring motion-blurred image on reconfigurable digital system

This work presents the hardware implementation of the RLA (Richardson-Lucy Algorithm) for image restoration task, in which the images are blurred by relative motion between camera and the scene. In this case the RLA was implemented in an FPGA-based platform using the hardware description language VHDL, and assuming the absence of additive noise in the capturing image system. The overall architecture is scalable from 3×3 to 9×9 mask sizes for the convolution steps of the RLA. The quality evaluation of the collected images was achieved using the SR-SIM (Spectral Residual Based Similarity) metric as well as by a visual verification of the images. The synthesis results and respective testing with real images are also presented in order to give support to video applications.