TY - GEN
T1 - B4MultiSR
T2 - 14th International Conference on Beyond Databases, Architectures and Structures, BDAS 2018 Held at the 24th IFIP World Computer Congress, WCC 2018
AU - Kostrzewa, Daniel
AU - Skonieczny, Łukasz
AU - Benecki, Paweł
AU - Kawulok, Michał
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2018.
PY - 2018
Y1 - 2018
N2 - Super-resolution reconstruction (SRR) methods consist in processing single or multiple images to increase their spatial resolution. Deployment of such techniques is particularly important, when high resolution image acquisition is associated with high cost or risk, like for medical or satellite imaging. Unfortunately, the existing SRR techniques are not sufficiently robust to be deployed in real-world scenarios, and no real-life benchmark to validate multiple-image SRR has been published so far. As gathering a set of images presenting the same scene at different spatial resolution is not a trivial task, the SRR methods are evaluated based on different assumptions, employing various metrics and datasets, often without using any ground-truth data. In this paper, we introduce a new multi-layer benchmark dataset for systematic evaluation of multiple-image SRR techniques with particular reference to satellite imaging. We hope that the new benchmark will help the researchers to improve the state of the art in SRR, making it suitable for real-world applications.
AB - Super-resolution reconstruction (SRR) methods consist in processing single or multiple images to increase their spatial resolution. Deployment of such techniques is particularly important, when high resolution image acquisition is associated with high cost or risk, like for medical or satellite imaging. Unfortunately, the existing SRR techniques are not sufficiently robust to be deployed in real-world scenarios, and no real-life benchmark to validate multiple-image SRR has been published so far. As gathering a set of images presenting the same scene at different spatial resolution is not a trivial task, the SRR methods are evaluated based on different assumptions, employing various metrics and datasets, often without using any ground-truth data. In this paper, we introduce a new multi-layer benchmark dataset for systematic evaluation of multiple-image SRR techniques with particular reference to satellite imaging. We hope that the new benchmark will help the researchers to improve the state of the art in SRR, making it suitable for real-world applications.
KW - Benchmark
KW - Dataset
KW - Image processing
KW - Super-resolution reconstruction
UR - https://www.scopus.com/pages/publications/85053854575
U2 - 10.1007/978-3-319-99987-6_28
DO - 10.1007/978-3-319-99987-6_28
M3 - Conference contribution
AN - SCOPUS:85053854575
SN - 9783319999869
T3 - Communications in Computer and Information Science
SP - 361
EP - 375
BT - Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings
A2 - Kozielski, Stanislaw
A2 - Mrozek, Dariusz
A2 - Kasprowski, Pawel
A2 - Malysiak-Mrozek, Bozena
A2 - Kostrzewa, Daniel
PB - Springer Verlag
Y2 - 18 September 2018 through 20 September 2018
ER -