The current state on usage of image mosaic algorithms
Intensive research has been done on image mosaic algorithms to improve the field of view through generated image mosaics. However, their usage varies from one field to another due to the challenges faced by image acquisition platforms. Moreover, the current imagery software packages used are computa...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Scientific African |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468227622003258 |
| _version_ | 1828118305399898112 |
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| author | Bose Alex Lungisani Caspar K. Lebekwe Adamu Murtala Zungeru Abid Yahya |
| author_facet | Bose Alex Lungisani Caspar K. Lebekwe Adamu Murtala Zungeru Abid Yahya |
| author_sort | Bose Alex Lungisani |
| collection | DOAJ |
| description | Intensive research has been done on image mosaic algorithms to improve the field of view through generated image mosaics. However, their usage varies from one field to another due to the challenges faced by image acquisition platforms. Moreover, the current imagery software packages used are computationally intensive to be used in real-time applications and are not economically affordable. Those that are open-source are limited due to the less amount of data used to test their mosaicing algorithms’ performance. Therefore, detailed knowledge of appropriate mosaic algorithms suitable for real-time applications is needed to produce mosaics with less computational time and efficient feature point detection. A comprehensive survey that categorizes existing mosaic algorithms’ adoption in various fields has not been done to the best of our knowledge. Firstly, we provide a comparison of the strengths, weaknesses, and uniqueness of the image mosaic algorithms across different fields, with emphasis on challenging issues, limitations, performance criteria, and mechanisms. Furthermore, this paper provides an up-to-date review of image mosaic algorithms in various domains as used in different fields. We further classify the usage of image mosaic algorithms based on the following domains: spatial, frequency, and combined spatial and frequency as used in agriculture, environmental monitoring, and medical imaging. In addition, an analysis was carried out on one of the promising algorithms based on improved SIFT with the aim of improvement. We then proposed an improved SIFT algorithm, which was then evaluated with an open-source algorithm and commercial software using structural similarity index measure (SSIM) and mosaicing computational times for mosaic accuracy and processing efficiency, respectively. Our approach demonstrated a significant improvement of more than 10% average on the mosaicing computational times for the five datasets used. Its mosaicing accuracy was found to be relatively within an acceptable range of above 90% averagely. |
| first_indexed | 2024-04-11T13:28:55Z |
| format | Article |
| id | doaj.art-6aa7ca512005422292213e4597f673b9 |
| institution | Directory Open Access Journal |
| issn | 2468-2276 |
| language | English |
| last_indexed | 2024-04-11T13:28:55Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Scientific African |
| spelling | doaj.art-6aa7ca512005422292213e4597f673b92022-12-22T04:21:53ZengElsevierScientific African2468-22762022-11-0118e01419The current state on usage of image mosaic algorithmsBose Alex Lungisani0Caspar K. Lebekwe1Adamu Murtala Zungeru2Abid Yahya3Department of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, BotswanaDepartment of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, BotswanaCorresponding author.; Department of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, BotswanaDepartment of Electrical, Computer and Telecommunications Engineering, Botswana International University of Science and Technology, BotswanaIntensive research has been done on image mosaic algorithms to improve the field of view through generated image mosaics. However, their usage varies from one field to another due to the challenges faced by image acquisition platforms. Moreover, the current imagery software packages used are computationally intensive to be used in real-time applications and are not economically affordable. Those that are open-source are limited due to the less amount of data used to test their mosaicing algorithms’ performance. Therefore, detailed knowledge of appropriate mosaic algorithms suitable for real-time applications is needed to produce mosaics with less computational time and efficient feature point detection. A comprehensive survey that categorizes existing mosaic algorithms’ adoption in various fields has not been done to the best of our knowledge. Firstly, we provide a comparison of the strengths, weaknesses, and uniqueness of the image mosaic algorithms across different fields, with emphasis on challenging issues, limitations, performance criteria, and mechanisms. Furthermore, this paper provides an up-to-date review of image mosaic algorithms in various domains as used in different fields. We further classify the usage of image mosaic algorithms based on the following domains: spatial, frequency, and combined spatial and frequency as used in agriculture, environmental monitoring, and medical imaging. In addition, an analysis was carried out on one of the promising algorithms based on improved SIFT with the aim of improvement. We then proposed an improved SIFT algorithm, which was then evaluated with an open-source algorithm and commercial software using structural similarity index measure (SSIM) and mosaicing computational times for mosaic accuracy and processing efficiency, respectively. Our approach demonstrated a significant improvement of more than 10% average on the mosaicing computational times for the five datasets used. Its mosaicing accuracy was found to be relatively within an acceptable range of above 90% averagely.http://www.sciencedirect.com/science/article/pii/S2468227622003258Frequency domain-basedImage mosaicRANSACSIFTSpatial domain-basedSURF |
| spellingShingle | Bose Alex Lungisani Caspar K. Lebekwe Adamu Murtala Zungeru Abid Yahya The current state on usage of image mosaic algorithms Scientific African Frequency domain-based Image mosaic RANSAC SIFT Spatial domain-based SURF |
| title | The current state on usage of image mosaic algorithms |
| title_full | The current state on usage of image mosaic algorithms |
| title_fullStr | The current state on usage of image mosaic algorithms |
| title_full_unstemmed | The current state on usage of image mosaic algorithms |
| title_short | The current state on usage of image mosaic algorithms |
| title_sort | current state on usage of image mosaic algorithms |
| topic | Frequency domain-based Image mosaic RANSAC SIFT Spatial domain-based SURF |
| url | http://www.sciencedirect.com/science/article/pii/S2468227622003258 |
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