Standard

Small objects detection in two-color images with spatially non-stationary background. / Kosykh, Valery P.; Gromilin, Gennady I.; Yakovenko, Nikolay S.

в: CEUR Workshop Proceedings, Том 2534, 12.01.2020, стр. 284-287.

Результаты исследований: Научные публикации в периодических изданиях › статья по материалам конференции › Рецензирование

Harvard

Kosykh, VP, Gromilin, GI & Yakovenko, NS 2020, 'Small objects detection in two-color images with spatially non-stationary background', CEUR Workshop Proceedings, Том. 2534, стр. 284-287.

APA

Kosykh, V. P., Gromilin, G. I., & Yakovenko, N. S. (2020). Small objects detection in two-color images with spatially non-stationary background. CEUR Workshop Proceedings, 2534, 284-287.

Vancouver

Kosykh VP, Gromilin GI, Yakovenko NS. Small objects detection in two-color images with spatially non-stationary background. CEUR Workshop Proceedings. 2020 янв. 12;2534:284-287.

Author

Kosykh, Valery P. ; Gromilin, Gennady I. ; Yakovenko, Nikolay S. / Small objects detection in two-color images with spatially non-stationary background. в: CEUR Workshop Proceedings. 2020 ; Том 2534. стр. 284-287.

BibTeX

@article{30a49bed83a042d6a2377e1ad528401b,
title = "Small objects detection in two-color images with spatially non-stationary background",
abstract = "A method for improving the reliability of detecting low-contrast small-sized objects in two-color images is considered by pre-suppressing their spatial-non-stationary background. Suppression is carried out by constructing a locally stationary background model using an optimal linear prediction. It is shown how the joint processing of images pair obtained in different spectral ranges affects the detection probability for a given false alarm probability",
keywords = "Low-contrast small-sized objects detection, Optimal linear prediction, Spatially non-stationary background, Two-color images",
author = "Kosykh, {Valery P.} and Gromilin, {Gennady I.} and Yakovenko, {Nikolay S.}",
note = "Publisher Copyright: Copyright {\textcopyright} 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).; 2019 All-Russian Conference {"}Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes{"}, SDM 2019 ; Conference date: 26-08-2019 Through 30-08-2019",
year = "2020",
month = jan,
day = "12",
language = "English",
volume = "2534",
pages = "284--287",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "CEUR-WS",

}

RIS

TY - JOUR

T1 - Small objects detection in two-color images with spatially non-stationary background

AU - Kosykh, Valery P.

AU - Gromilin, Gennady I.

AU - Yakovenko, Nikolay S.

N1 - Publisher Copyright: Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

PY - 2020/1/12

Y1 - 2020/1/12

N2 - A method for improving the reliability of detecting low-contrast small-sized objects in two-color images is considered by pre-suppressing their spatial-non-stationary background. Suppression is carried out by constructing a locally stationary background model using an optimal linear prediction. It is shown how the joint processing of images pair obtained in different spectral ranges affects the detection probability for a given false alarm probability

AB - A method for improving the reliability of detecting low-contrast small-sized objects in two-color images is considered by pre-suppressing their spatial-non-stationary background. Suppression is carried out by constructing a locally stationary background model using an optimal linear prediction. It is shown how the joint processing of images pair obtained in different spectral ranges affects the detection probability for a given false alarm probability

KW - Low-contrast small-sized objects detection

KW - Optimal linear prediction

KW - Spatially non-stationary background

KW - Two-color images

UR - http://www.scopus.com/inward/record.url?scp=85078521155&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85078521155

VL - 2534

SP - 284

EP - 287

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

T2 - 2019 All-Russian Conference "Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes", SDM 2019

Y2 - 26 August 2019 through 30 August 2019

ER -

ID: 34226766