Title :
SAR segmentation algorithms: a quantitative assessment
Author :
Frery, Alejandro C. ; Lucca, Eduardo V D ; Freitas, Corina Da C ; Sant´Anna, S.J.S.
Author_Institution :
Dept. de Inf., Univ. Fed. de Pernambuco, Recife, Brazil
Abstract :
This paper compares the performance of two segmentation algorithms, the MUM (Merge Using Moments) and RWSEG, using simulated synthetic aperture radar (SAR) data. This comparison is performed from both the qualitative and quantitative points of view, and carried out using synthetic images that contain regions with different homogeneity degrees, aiming at land use applications. The process for obtaining simulated images consists of creating an idealized classes image (a phantom), which summarizes the main geometric and topologic characteristics of Amazonian targets. Then a statistical model of observations from each class is proposed, and a Monte Carlo experience is performed
Keywords :
geophysical signal processing; geophysical techniques; image segmentation; radar imaging; remote sensing by radar; synthetic aperture radar; terrain mapping; Amazon; MUM; Merge Using Moments; Monte Carlo simulation; RWSEG; SAR; SAR segmentation algorithm; geophysical measurement technique; homogeneity degree; idealized classes image; image segmentation; land surface; land use; phantom; quantitative assessment; radar imaging; radar remote sensing; statistical model; synthetic aperture radar; synthetic image; terrain mapping; Algorithm design and analysis; Image analysis; Image edge detection; Image segmentation; Merging; Performance analysis; Performance evaluation; Random variables; Software algorithms; Synthetic aperture radar;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Conference_Location :
Hamburg
Print_ISBN :
0-7803-5207-6
DOI :
10.1109/IGARSS.1999.774599
