bibtype C - Conference Paper (international conference)
ARLID 0508020
utime 20240103222501.8
mtime 20190904235959.9
SCOPUS 85072869244
DOI 10.1007/978-3-030-29888-3_34
title (primary) (eng) Robust Histogram Estimation Under Gaussian Noise
specification
page_count 12 s.
media_type P
serial
ARLID cav_un_epca*0508720
ISBN 978-3-030-29929-3
title Computer Analysis of Images and Patterns : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings
page_num 421-432
publisher
place Cham
name Springer
year 2019
editor
name1 Vento
name2 M.
editor
name1 Percannella
name2 G.
editor
name1 Colantonio
name2 S.
editor
name1 Giorgi
name2 D.
editor
name1 Matuszewski
name2 B. J.
editor
name1 Kerdegari
name2 H.
editor
name1 Razaak
name2 M.
keyword Gaussian additive noise
keyword Multidimensional histogram
keyword Invariant characteristics
keyword Moments
keyword Projection operator
author (primary)
ARLID cav_un_auth*0336802
name1 Kostková
name2 Jitka
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101087
name1 Flusser
name2 Jan
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2019/ZOI/kostkova-0508020.pdf
cas_special
project
ARLID cav_un_auth*0360229
project_id GA18-07247S
agency GA ČR
abstract (eng) We present a novel approach to description of a multidimensional image histogram insensitive with respect to an additive Gaussian noise in the image. The proposed quantities, although calculated from the histogram of the noisy image, represent the histogram of the original clear image. Noise estimation, image denoising and histogram deconvolution are avoided.We construct projection operators, that divide the histogram into non-Gaussian and Gaussian part, which is consequently removed to ensure the invariance. The descriptors are based on the moments of the histogram of the noisy image. The method can be used in a histogrambased image retrieval systems.
action
ARLID cav_un_auth*0380252
name International Conference on Computer Analysis of Images and Patterns, CAIP 2019 /18./
dates 20190902
mrcbC20-s 20190906
place Salerno
country IT
RIV JD
FORD0 20000
FORD1 20200
FORD2 20206
reportyear 2020
num_of_auth 2
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0299551
confidential S
contract
name Consent to publish
date 20190528
note Copyright
arlyear 2019
mrcbTft \nSoubory v repozitáři: kostkova-0508020-Consent to publish.pdf
mrcbU14 85072869244 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0508720 Computer Analysis of Images and Patterns : CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Springer 2019 Cham 421 432 978-3-030-29929-3 Communications in Computer and Information Science 1089
mrcbU67 340 Vento M.
mrcbU67 340 Percannella G.
mrcbU67 340 Colantonio S.
mrcbU67 340 Giorgi D.
mrcbU67 340 Matuszewski B. J.
mrcbU67 340 Kerdegari H.
mrcbU67 340 Razaak M.