Accelerating block-matching and 3D filtering method for image denoising on GPUs

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372625" target="_blank" >RIV/00216208:11320/17:10372625 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=.roh9wweaJ" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=.roh9wweaJ</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11554-017-0737-9" target="_blank" >10.1007/s11554-017-0737-9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Accelerating block-matching and 3D filtering method for image denoising on GPUs

Popis výsledku v původním jazyce

Denoising photographs and video recordings is an important task in the domain of image processing. In this paper, we focus on block-matching and 3D filtering (BM3D) algorithm, which uses self-similarity of image blocks to improve the noise-filtering process. Even though this method has achieved quite impressive results in the terms of denoising quality, it is not being widely used. One of the reasons is a fact that the method is extremely computationally demanding. In this paper, we present a CUDA-accelerated implementation which increased the image processing speed significantly and brings the BM3D method much closer to real applications. The GPU implementation of the BM3D algorithm is not as straightforward as the implementation of simpler image processing methods, and we believe that some parts (especially the block-matching) can be utilized separately or provide guidelines for similar algorithms.

Název v anglickém jazyce

Accelerating block-matching and 3D filtering method for image denoising on GPUs

Popis výsledku anglicky

Denoising photographs and video recordings is an important task in the domain of image processing. In this paper, we focus on block-matching and 3D filtering (BM3D) algorithm, which uses self-similarity of image blocks to improve the noise-filtering process. Even though this method has achieved quite impressive results in the terms of denoising quality, it is not being widely used. One of the reasons is a fact that the method is extremely computationally demanding. In this paper, we present a CUDA-accelerated implementation which increased the image processing speed significantly and brings the BM3D method much closer to real applications. The GPU implementation of the BM3D algorithm is not as straightforward as the implementation of simpler image processing methods, and we believe that some parts (especially the block-matching) can be utilized separately or provide guidelines for similar algorithms.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GP14-14292P" target="_blank" >GP14-14292P: Nasazení moderních paralelních architektur ve specifických oblastech databázových systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Real-Time Image Processing

ISSN

1861-8200

e-ISSN

—

Svazek periodika

Neuveden

Číslo periodika v rámci svazku

29.11.2017

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

000501450300026

EID výsledku v databázi Scopus

2-s2.0-85035311240