Efficient hardware implementation of the Richardson-Lucy algorithm for restoring motion-blurred image on reconfigurable digital system
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Universidade Federal de Minas Gerais
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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.
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Processamento de imagens -- Técnicas digitais, Engenharia elétrica
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Image restoration , Convolution , Mathematical model , Hardware , Computer architecture , Deconvolution , Measurement, Richardson-Lucy Algorithm , Motion-Blurred Image Restoration , FPGA, Hardware Implementation , Scalable , Additive Noise , Distortion , Computer Vision , Input Image , Image Size , Convolution Operation , Singular Value Decomposition , Correction Process , Peak Signal-to-noise Ratio , Point Spread Function , Image Edge , Mathematical Operations , Inversion Process , Ordered Subset Expectation Maximization , Clock Cycles , Hardware Architecture , Convolution Process , Restoration Quality , Embedded System
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https://ieeexplore.ieee.org/document/7724056