Earth remote sensing data processing for obtaining vegetation types maps
In this paper, we propose an earth remote sensing data processing technology for obtaining vegetation types maps. The technology includes the following steps: obtaining superpixel representation of an image, calculating superpixel features, K-Means clustering of superpixels by a user-defined trainin...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Samara National Research University
2018-10-01
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| Series: | Компьютерная оптика |
| Subjects: | |
| Online Access: | http://computeroptics.smr.ru/KO/PDF/KO42-5/420518.pdf |
| _version_ | 1818313071496527872 |
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| author | Anna Varlamova Anna Denisova Vladislav Sergeyev |
| author_facet | Anna Varlamova Anna Denisova Vladislav Sergeyev |
| author_sort | Anna Varlamova |
| collection | DOAJ |
| description | In this paper, we propose an earth remote sensing data processing technology for obtaining vegetation types maps. The technology includes the following steps: obtaining superpixel representation of an image, calculating superpixel features, K-Means clustering of superpixels by a user-defined training sample, and obtaining vegetation types maps. When compared to other solutions, the major difference of the proposed technology is the ability to combine superpixel segmentation and feature calculation into a single process in one pass of an image that reduces the computational complexity. Another difference lies in the way of forming a sample dataset using superpixel representation of an image. The advantages of the proposed technology are the use of a smaller training dataset and a higher classification quality in comparison with the elemental classification. |
| first_indexed | 2024-12-13T08:27:55Z |
| format | Article |
| id | doaj.art-9302be1b79154dcb8204fd81969090dd |
| institution | Directory Open Access Journal |
| issn | 0134-2452 2412-6179 |
| language | English |
| last_indexed | 2024-12-13T08:27:55Z |
| publishDate | 2018-10-01 |
| publisher | Samara National Research University |
| record_format | Article |
| series | Компьютерная оптика |
| spelling | doaj.art-9302be1b79154dcb8204fd81969090dd2022-12-21T23:53:51ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792018-10-0142586487610.18287/2412-6179-2018-42-5-864-876Earth remote sensing data processing for obtaining vegetation types mapsAnna Varlamova 0Anna Denisova1Vladislav Sergeyev2Samara University, Moskovskoe Shosse 34А, Samara, RussiaSamara University, Moskovskoe Shosse 34А, Samara, RussiaSamara University, Moskovskoe Shosse 34А, Samara, Russia; Image Processing Systems Institute, Branch of the Federal Scientific Research Centre “Crystallography and Photonics” of Russian Academy of Sciences, Molodogvardeiskaya st. 151, Samara, RussiaIn this paper, we propose an earth remote sensing data processing technology for obtaining vegetation types maps. The technology includes the following steps: obtaining superpixel representation of an image, calculating superpixel features, K-Means clustering of superpixels by a user-defined training sample, and obtaining vegetation types maps. When compared to other solutions, the major difference of the proposed technology is the ability to combine superpixel segmentation and feature calculation into a single process in one pass of an image that reduces the computational complexity. Another difference lies in the way of forming a sample dataset using superpixel representation of an image. The advantages of the proposed technology are the use of a smaller training dataset and a higher classification quality in comparison with the elemental classification.http://computeroptics.smr.ru/KO/PDF/KO42-5/420518.pdfsuperpixel segmentationclusteringvegetation regionspercentage composition |
| spellingShingle | Anna Varlamova Anna Denisova Vladislav Sergeyev Earth remote sensing data processing for obtaining vegetation types maps Компьютерная оптика superpixel segmentation clustering vegetation regions percentage composition |
| title | Earth remote sensing data processing for obtaining vegetation types maps |
| title_full | Earth remote sensing data processing for obtaining vegetation types maps |
| title_fullStr | Earth remote sensing data processing for obtaining vegetation types maps |
| title_full_unstemmed | Earth remote sensing data processing for obtaining vegetation types maps |
| title_short | Earth remote sensing data processing for obtaining vegetation types maps |
| title_sort | earth remote sensing data processing for obtaining vegetation types maps |
| topic | superpixel segmentation clustering vegetation regions percentage composition |
| url | http://computeroptics.smr.ru/KO/PDF/KO42-5/420518.pdf |
| work_keys_str_mv | AT annavarlamova earthremotesensingdataprocessingforobtainingvegetationtypesmaps AT annadenisova earthremotesensingdataprocessingforobtainingvegetationtypesmaps AT vladislavsergeyev earthremotesensingdataprocessingforobtainingvegetationtypesmaps |