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

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dc.creatorOscar Anacona-Mosquera
dc.creatorJanier Arias García
dc.creatorDaniel M. Munoz
dc.creatorCarlos H. Llanos
dc.date.accessioned2025-03-25T14:57:16Z
dc.date.accessioned2025-09-09T01:09:52Z
dc.date.available2025-03-25T14:57:16Z
dc.date.issued2016
dc.identifier.doi10.1109/SBCCI.2016.7724056
dc.identifier.urihttps://hdl.handle.net/1843/80897
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.rightsAcesso Restrito
dc.subjectProcessamento de imagens -- Técnicas digitais
dc.subjectEngenharia elétrica
dc.subject.otherImage restoration , Convolution , Mathematical model , Hardware , Computer architecture , Deconvolution , Measurement
dc.subject.otherRichardson-Lucy Algorithm , Motion-Blurred Image Restoration , FPGA
dc.subject.otherHardware 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
dc.titleEfficient hardware implementation of the Richardson-Lucy algorithm for restoring motion-blurred image on reconfigurable digital system
dc.typeArtigo de evento
local.citation.spage1
local.description.resumoThis 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.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ieeexplore.ieee.org/document/7724056

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