Improving multiple-image super-resolution for mobile devices through image alignment selection
Multiple-image super-resolution (MISR) attempts to recover a high-resolution (HR) image from a set of low resolution (LR) images. In this paper, we present a mobile MISR tailored to work for a wide range of mobile devices. Our technique aims to address misalignment issues from a previous work and fu...
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| Main Authors: | , |
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| Format: | text |
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Animo Repository
2018
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| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/3487 https://animorepository.dlsu.edu.ph/context/faculty_research/article/4489/viewcontent/JWSCG.2018.26.2.7 |
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| Institution: | De La Salle University |
| Summary: | Multiple-image super-resolution (MISR) attempts to recover a high-resolution (HR) image from a set of low resolution (LR) images. In this paper, we present a mobile MISR tailored to work for a wide range of mobile devices. Our technique aims to address misalignment issues from a previous work and further enhance the quality of HR images produced. The proposed architecture is used to implement a prototype application that is freely available at Google Play Store, titled Eagle-Eye HD Camera. The system is divided into the following modules: Input Module, Edge Detection Module, Image Selection Module, Image Alignment Module, Alignment Selection Module and Image Fusion Module. We assessed the quality of HR images produced by our mobile MISR, through an online survey, as well as compare it with other related SR works. Performance time was also measured. A total of 114 respondents have participated in the survey, where majority of respondents preferred our approach. Our approach is observed to be comparable with other SR works in terms of visual quality and performance time, and guaranteed to work in a mobile environment. © 2018, Vaclav Skala Union Agency. All rights reserved. |
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