Combined No-Reference Image Quality Metrics for Visual Quality Assessment Optimized for Remote Sensing Images

Andrii Rubel; Oleg Ieremeiev; Vladimir Lukin; Jarosław Fastowicz; Krzysztof Piotr Okarma

doi:10.3390/app12041986

Combined No-Reference Image Quality Metrics for Visual Quality Assessment Optimized for Remote Sensing Images

Abstrakt

No-reference image quality assessment is one of the most demanding areas of image analysis for many applications where the results of the analysis should be strongly correlated with the quality of an input image and the corresponding reference image is unavailable. One of the examples might be remote sensing since the transmission of such obtained images often requires the use of lossy compression and they are often distorted, e.g., by the presence of noise and blur. Since the practical usefulness of acquired and/or preprocessed images is directly related to their quality, there is a need for the development of reliable and adequate no-reference metrics that do not need any reference images. As the performance and universality of many existing metrics are quite limited, one of the possible solutions is the design and application of combined metrics. Several possible approaches to their composition have been previously proposed and successfully used for full-reference metrics. In the paper, three possible approaches to the development and optimization of no-reference combined metrics are investigated and verified for the dataset of images containing distortions typical for remote sensing. The proposed approach leads to good results, significantly improving the correlation of the obtained results with subjective quality scores.

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Autorzy (5)

Andrii Rubel
Oleg Ieremeiev
Vladimir Lukin
Jarosław Fastowicz dr inż.
- Wydział Elektryczny
- Zachodniopomorski Uniwersytet Technologiczny w Szczecinie
Krzysztof Piotr Okarma prof. dr hab. inż.
- Wydział Elektryczny
- Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

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Informacje szczegółowe

Kategoria:: Publikacja w czasopiśmie
Typ:: Publikacja w czasopiśmie
Opublikowano w:: Applied Sciences-Basel nr 12, wydanie 4,
ISSN: 2076-3417
ISSN:: 2076-3417
Rok wydania:: 2022
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/app12041986
Weryfikacja:: Brak weryfikacji