entropy Article Entropy-Based Combined Metric for Automatic Objective Quality Assessment of Stitched Panoramic Images Krzysztof Okarma 1, * , Wojciech Chlewicki 1 , Mateusz Kopytek 1 , Beata Marciniak 2 and Vladimir Lukin 3   Citation: Okarma, K.; Chlewicki, W.; Kopytek, M.; Marciniak, B.; Lukin, V. Entropy-Based Combined Metric for Automatic Objective Quality Assessment of Stitched Panoramic Images. Entropy 2021, 23, 1525. https://doi.org/10.3390/e23111525 Academic Editors: Michal Choras, Robert Burduk, Agata Gielczyk, Rafal Kozik and Tomasz Marciniak Received: 8 October 2021 Accepted: 15 November 2021 Published: 17 November 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1 Department of Signal Processing and Multimedia Engineering, West Pomeranian University of Technology in Szczecin, 70-313 Szczecin, Poland; wojciech.chlewicki@zut.edu.pl (W.C.); km46880@zut.edu.pl (M.K.) 2 Faculty of Telecommunications, Computer Science and Electrical Engineering, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland; beata.marciniak@pbs.edu.pl 3 Department of Information and Communication Technologies, National Aerospace University, 61070 Kharkov, Ukraine; lukin@ai.kharkov.com * Correspondence: okarma@zut.edu.pl Abstract: Quality assessment of stitched images is an important element of many virtual reality and remote sensing applications where the panoramic images may be used as a background as well as for navigation purposes. The quality of stitched images may be decreased by several factors, including geometric distortions, ghosting, blurring, and color distortions. Nevertheless, the specificity of such distortions is different than those typical for general-purpose image quality assessment. Therefore, the necessity of the development of new objective image quality metrics for such type of emerging applications becomes obvious. The method proposed in the paper is based on the combination of features used in some recently proposed metrics with the results of the local and global image entropy analysis. The results obtained applying the proposed combined metric have been verified using the ISIQA database, containing 264 stitched images of 26 scenes together with the respective subjective Mean Opinion Scores, leading to a significant increase of its correlation with subjective evaluation results. Keywords: image quality assessment; stitched images; panoramic images; image analysis; image entropy 1. Introduction Panoramic images, constructed as a result of image stitching operation conducted for a series of constituent images with partially overlapping regions, may suffer from various distortions, including blur, ghosting artifacts, and quite well visible geometric and color distortions. The presence of such issues decreases the perceived image quality and in some cases may be unacceptable from an aesthetic point of view. Although modern cameras and smartphones are usually equipped with software functions making it possible to properly register the overlapping areas of individual photos to create panoramic images, some additional requirements should be fulfilled by users during the recording to prevent such problems. Nevertheless, the growing availability of software and hardware solutions causes higher popularity of panoramic images which may be useful, e.g., as wide background images, in virtual reality scenarios, as well as in mobile robotics for the Visual Simultaneous Localization and Mapping (VSLAM) applications. Considering the modern applications of image stitching and image registration algo- rithms, related to the use of cameras mounted on mobile robots, the quality of obtained panoramic images is very important due to potential errors in vision-based control of their motion. In the case of decreased image quality, such images might be removed from the analysis to prevent their influence on the robot’s control. Another interesting direction of such research in mobile robotics concerns the fusion of images acquired by unmanned aerial vehicles (UAVs) [1,2]. One of the most relevant factors, influencing the final quality of the panoramic images, is the appropriate choice of distinctive image features used to match the same regions Entropy 2021, 23, 1525. https://doi.org/10.3390/e23111525 https://www.mdpi.com/journal/entropy