Efficiency Increasing of No‐Reference Image Quality Assessment in UAV Applications

Oleg Ieremeiev, Vladimir Lukin, Krzysztof Okarma, Karen Egiazarian

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

Abstrakti

Unmanned aerial vehicle (UAV) imaging is a dynamically developing field, where the effectiveness of imaging applications highly depends on quality of the acquired images. No-reference image quality assessment is widely used for quality control and image processing management. However, there is a lack of accuracy and adequacy of existing quality metrics for human visual perception. In this paper, we demonstrate that this problem persists for typical applications of UAV images. We present a methodology to improve the efficiency of visual quality assessment by existing metrics for images obtained from UAVs, and introduce a method of combining quality metrics with the optimal selection of the elementary metrics used in this combination. A combined metric is designed based on a neural network trained to utilize subjective assessments of visual quality. The metric was tested using the TID2013 image database and a set of real UAV images with embedded distortions. Verification results have demonstrated the robustness and accuracy of the proposed metric.

AlkuperäiskieliEnglanti
OtsikkoProceedings of The Sixth International Workshop on Computer Modeling and Intelligent Systems (CMIS 2023)
KustantajaCEUR-WS
Sivut246-260
Sivumäärä15
TilaJulkaistu - 2023
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Workshop on Computer Modeling and Intelligent Systems (CMIS) - , Ukraina
Kesto: 3 toukok. 20233 toukok. 2023

Julkaisusarja

NimiCEUR Workshop Proceedings
KustantajaCEUR-WS
Vuosikerta3392
ISSN (elektroninen)1613-0073

Conference

ConferenceInternational Workshop on Computer Modeling and Intelligent Systems (CMIS)
Maa/AlueUkraina
Ajanjakso3/05/233/05/23

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