- Tytuł:
- Performance of Unsupervised Change Detection Method Based on PSO and K-means Clustering for SAR Images
- Autorzy:
-
Shehab, Jinan N.
Abdulkadhim, Hussein A. - Powiązania:
- https://bibliotekanauki.pl/articles/1844494.pdf
- Data publikacji:
- 2021
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
change detection
k-means clustering
multitemporal satellite image
PSO
Gabor wavelet filter
remote sensing - Opis:
- This paper presents unsupervised change detection method to produce more accurate change map from imbalanced SAR images for the same land cover. This method is based on PSO algorithm for image segmentation to layers which classify by Gabor Wavelet filter and then K-means clustering to generate new change map. Tests are confirming the effectiveness and efficiency by comparison obtained results with the results of the other methods. Integration of PSO with Gabor filter and k-means will providing more and more accuracy to detect a least changing in objects and terrain of SAR image, as well as reduce the processing time.
- Źródło:
-
International Journal of Electronics and Telecommunications; 2021, 67, 3; 403-408
2300-1933 - Pojawia się w:
- International Journal of Electronics and Telecommunications
- Dostawca treści:
- Biblioteka Nauki
Artykuł