Academic Journal
Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview
| Title: | Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview |
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| Authors: | Anju Asokan, J. Anitha, Monica Ciobanu, Andrei Gabor, Antoanela Naaji, D. Jude Hemanth |
| Source: | Applied Sciences, Vol 10, Iss 12, p 4207 (2020) |
| Publisher Information: | MDPI AG, 2020. |
| Publication Year: | 2020 |
| Collection: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| Subject Terms: | remote sensing, change detection, fusion, feature extraction, segmentation, classification, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| More Details: | Historical maps classification has become an important application in today’s scenario of everchanging land boundaries. Historical map changes include the change in boundaries of cities/states, vegetation regions, water bodies and so forth. Change detection in these regions are mainly carried out via satellite images. Hence, an extensive knowledge on satellite image processing is necessary for historical map classification applications. An exhaustive analysis on the merits and demerits of many satellite image processing methods are discussed in this paper. Though several computational methods are available, different methods perform differently for the various satellite image processing applications. Wrong selection of methods will lead to inferior results for a specific application. This work highlights the methods and the suitable satellite imaging methods associated with these applications. Several comparative analyses are also performed in this work to show the suitability of several methods. This work will help support the selection of innovative solutions for the different problems associated with satellite image processing applications. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2076-3417 |
| Relation: | https://www.mdpi.com/2076-3417/10/12/4207; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app10124207 |
| Access URL: | https://doaj.org/article/0e9ff80e62bd48c996b38f879fa89057 |
| Accession Number: | edsdoj.0e9ff80e62bd48c996b38f879fa89057 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 20763417 |
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| DOI: | 10.3390/app10124207 |
| Published in: | Applied Sciences |
| Language: | English |