TY - JOUR
T1 - The current state on usage of image mosaic algorithms
AU - Lungisani, Bose Alex
AU - Lebekwe, Caspar K.
AU - Zungeru, Adamu Murtala
AU - Yahya, Abid
N1 - Funding Information:
Appreciation goes to the Botswana International University of Science and Technology for providing various research platforms and resources used in this research. Also, much appreciation goes to the Department of Electrical, Computer, and Telecommunications for their motivation and support.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/11
Y1 - 2022/11
N2 - 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.
AB - 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.
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U2 - 10.1016/j.sciaf.2022.e01419
DO - 10.1016/j.sciaf.2022.e01419
M3 - Review article
AN - SCOPUS:85140879785
SN - 2468-2276
VL - 18
JO - Scientific African
JF - Scientific African
M1 - e01419
ER -