A New FPGA-Based Architecture for Iterative and Space-Variant Image Processing

We propose a strategy to realize an innovative FPGA-based architecture able to speed up the Lucy-Richardson algorithm (LRA) for space-variant image deconvolution. The architecture exploits the possibility to distribute data into different memory blocks in the FPGA. In such a way, the algorithm execution is split into several channels operating in parallel. Since the LRA is implemented via an iterative and space-variant convolution, the approach adopted in this paper can be exploited in other similar image processing algorithms.