Effects of parameter tuning and de-speckle filtering on the accuracy of SAR image classification based on gray-level co-occurrence matrix features

Author

Bruzzone, L. ; Serpico, S.B. ; Vernazza, G.

Author_Institution

Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy

Volume

2

fYear

1997

fDate

3-8 Aug 1997

Firstpage

764

Abstract

The results of an experimental investigation of the use of textural features computed from the gray-level co-occurrence matrix for synthetic aperture radar (SAR) image classification are reported and discussed. The investigation, carried out on SAR images acquired with the SIR-C/X-SAR sensor in an Italian agricultural area, makes it possible to derive interesting information about the computation modalities and the effectiveness of the above textural features

Keywords

geophysical signal processing; geophysical techniques; image classification; image texture; radar imaging; remote sensing by radar; spaceborne radar; speckle; synthetic aperture radar; Italy; SAR; SAR images; SIR-C X-SAR; agriculture; computation modalities; de-speckle filtering; geophysical measurement technique; gray-level co-occurrence matrix features; image classification; image texture; land surface; parameter tuning; radar imaging; radar remote sensing; spaceborne radar; synthetic aperture radar; terrain mapping; Adaptive optics; Electronic mail; Filtering; Image classification; Image sensors; Optical filters; Optical sensors; Pixel; Sensor phenomena and characterization; Synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International

Print_ISBN

0-7803-3836-7

Type

conf

DOI

10.1109/IGARSS.1997.615250

Filename

615250