Abstract
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.
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Marsi, S., Carrato, S., Ramponi, G. (2017). A New FPGA-Based Architecture for Iterative and Space-Variant Image Processing. In: De Gloria, A. (eds) Applications in Electronics Pervading Industry, Environment and Society. ApplePies 2016. Lecture Notes in Electrical Engineering, vol 409. Springer, Cham. https://doi.org/10.1007/978-3-319-47913-2_2
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DOI: https://doi.org/10.1007/978-3-319-47913-2_2
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