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Doctoral Thesis
Author of thesis: Ing. Marek Šimka
Acad. year: 2025/2026
Supervisor: doc. Ing. Ladislav Polák, Ph.D.
Reviewers: Ing. Lukáš Krasula, Ph.D., Assoc. Prof. Jesús Gutiérrez Sánchez
The storage and transmission requirements of omnidirectional (360°) images are significantly higher than those of conventional 2D content. Therefore, effective compression algorithms and reliable image quality assessment (IQA) methods are essential for their practical deployment. This doctoral thesis addresses the challenge of evaluating the visual quality of omnidirectional images compressed by emerging codecs, reflecting a real-world scenario in which file size must be reduced while maintaining a high level of perceived visual quality. First, it examines the applicability of emerging compression standards (JPEG XL, HEIC, AVIF) to 360° images and evaluates their performance using commonly employed IQA metrics. Next, it introduces the Omnidirectional Image Quality Assessment Database (OMNIQAD), a unique dataset that includes distortions caused by recent compression standards (the first public dataset with JPEG XL and AVIF) as well as noise-based distortions, thereby enabling reproducible research. A large-scale subjective experiment, further extended with eye-tracking data, enriches the database and provides valuable insights into how user-related factors (e.g., VR experience, visual impairments) influence perceived quality. The thesis then analyses the performance of conventional objective IQA metrics on compressed 360° images against subjective ratings. Building on these findings, a novel fusion-based omnidirectional IQA (OIQA) method is proposed. This method integrates multiple feature metrics to achieve superior correlation with human perception. Its effectiveness is validated on two datasets (OMNIQAD and CVIQ), with preliminary comparisons against deep learning-based approaches. Overall, the dissertation provides original findings on OIQA of compressed omnidirectional images, introduces OMNIQAD as a benchmarking resource for further research, and proposes an enhanced feature-fusion methodology validated across multiple datasets.
Omnidirectional image, 360° image, Virtual Reality, VR content, Image database, Image quality assessment, Image compression, Emerging compression algorithms, JPEG, JPEG XL, HEIC, AVIF
Date of defence
16.12.2025
Result of the defence
Defended (thesis was successfully defended)
Process of defence
Ph.D. student Ing. Marek Simka presented the core of his work, familiarized the committee with his motivation for addressing the area of evaluating the quality of multimedia systems for virtual reality, and with the results achieved. After reading the reviews, he responded to a number of questions and comments from the reviewers and answered questions from the committee members. In conclusion, the committee agreed that the student had demonstrated the ability to conduct independent scientific work at a high level and unanimously agreed that Marek Simka had met the conditions for the award of the academic title of Doctor.
Language of thesis
English
Faculty
Fakulta elektrotechniky a komunikačních technologií
Department
Department of Radio Electronics
Study programme
Electronics and Communication Technologies (DPC-EKT)
Composition of Committee
prof. Ing. Aleš Prokeš, Ph.D. (předseda) Ing. Martin Řeřábek, Ph.D. (člen) prof. Ing. Tomáš Kratochvíl, Ph.D. (člen) doc. Ing. Stanislav Vítek, Ph.D. (člen) prof. Ing. Kamil Říha, Ph.D. (člen) Assoc. Prof. Jesús Gutiérrey (člen) Ing. Lukáš Krasula, Ph.D. (člen)
Supervisor’s reportdoc. Ing. Ladislav Polák, Ph.D.
Reviewer’s reportIng. Lukáš Krasula, Ph.D.
Reviewer’s reportAssoc. Prof. Jesús Gutiérrez Sánchez
Responsibility: Mgr. et Mgr. Hana Odstrčilová