@inproceedings{772756d2ae4e4466a5af85b6d0ef6868,
title = "Enhancing the Resolution of Satellite Images Using the Best Matching Image Fragment",
abstract = "Due to very high costs and a long revisit time, it is challenging to obtain good quality satellite images of the area of interest. As a result, super resolution reconstruction (SRR) methods which allow for creating a high-resolution (HR) image based on single or multiple low-resolution (LR) observations are being extensively developed. In this paper, we propose a few improvements to well-known single-image SRR technique based on a dictionary of pairs of matched LR and HR image fragments. The modifications concern both increasing the number of pairs of images fragments and the reconstruction algorithm itself in order to achieve visually pleasing results. This allows us to increase the quality of newly produced HR satellite images what is supported by conducted experiments.",
keywords = "Dictionary of matched fragments, Image processing, Satellite image, Single-image super-resolution reconstruction",
author = "Daniel Kostrzewa and Pawel Benecki and Lukasz Jenczmyk",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019 ; Conference date: 08-04-2019 Through 11-04-2019",
year = "2019",
doi = "10.1007/978-3-030-14799-0\_50",
language = "English",
isbn = "9783030147983",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "576--586",
editor = "Gaol, \{Ford Lumban\} and Nguyen, \{Ngoc Thanh\} and Nguyen, \{Ngoc Thanh\} and Bogdan Trawi{\'n}ski and Tzung-Pei Hong",
booktitle = "Intelligent Information and Database Systems - 11th Asian Conference, ACIIDS 2019, Proceedings",
address = "Germany",
}