Segmentation method based on multiobjective optimization for very high spatial resolution satellite images
| Autor: | Omar El Kadmiri, R Zennouhi, Salah Eddine Mechkouri, Lhoussaine Masmoudi, Saleh El Joumani |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Satellite image VHSR (Quickbird)
Biometrics Computer science Entropy Otsu Scale-space segmentation lcsh:TK7800-8360 02 engineering and technology Multicriterion Grayscale Multi-objective optimization Segmentation Histogram 0202 electrical engineering electronic engineering information engineering Computer vision Electrical and Electronic Engineering K-means business.industry lcsh:Electronics k-means clustering 020206 networking & telecommunications 020207 software engineering Image segmentation Signal Processing Artificial intelligence business Information Systems |
| Zdroj: | EURASIP Journal on Image and Video Processing, Vol 2017, Iss 1, Pp 1-9 (2017) |
| ISSN: | 1687-5281 |
| DOI: | 10.1186/s13640-016-0161-2 |
| Popis: | In this paper, a new multicriterion segmentation method has been proposed to be applied to satellite image of very high spatial resolution (VHSR). It is consisted of the following process: For each region of the grayscale image, a center of gravity has been calculated and it has been also selected a threshold for its histogram. According to a certain criteria, this approach has been based on the separation of the different classes of grayscale in an optimal way. The proposed approach has been tested on synthetic images, and then has applied to an urban environment for the classification of data in Quickbird images. The selected zone of study has been laid in Skhirate-Témara province, northwest of Morocco. Which is based on the Levine and Nazif criterion, this segmentation technique has given promising results compared those obtained using OTSU and K-means methods. |
| Databáze: | OpenAIRE |
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