A Novel Technique Based on the Combination of Labeled Co-Occurrence Matrix and Variogram for the Detection of Built-up Areas in High-Resolution SAR ImagesReport as inadecuate




A Novel Technique Based on the Combination of Labeled Co-Occurrence Matrix and Variogram for the Detection of Built-up Areas in High-Resolution SAR Images - Download this document for free, or read online. Document in PDF available to download.

1

College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China

2

Department of Information Engineering and Computer Science, University of Trento, Trento 38123, Italy





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Abstract Interests in synthetic aperture radar SAR data analysis is driven by the constantly increased spatial resolutions of the acquired images, where the geometries of scene objects can be better defined than in lower resolution data. This paper addresses the problem of the built-up areas extraction in high-resolution HR SAR images, which can provide a wealth of information to characterize urban environments. Strong backscattering behavior is one of the distinct characteristics of built-up areas in a SAR image. However, in practical applications, only a small portion of pixels characterizing the built-up areas appears bright. Thus, specific texture measures should be considered for identifying these areas. This paper presents a novel texture measure by combining the proposed labeled co-occurrence matrix technique with the specific spatial variability structure of the considered land-cover type in the fuzzy set theory. The spatial variability is analyzed by means of variogram, which reflects the spatial correlation or non-similarity associated with a particular terrain surface. The derived parameters from the variograms are used to establish fuzzy functions to characterize the built-up class and non built-up class, separately. The proposed technique was tested on TerraSAR-X images acquired of Nanjing China and Barcelona Spain, and on a COSMO-SkyMed image acquired of Hangzhou China. The obtained classification accuracies point out the effectiveness of the proposed technique in identifying and detecting built-up areas. View Full-Text

Keywords: synthetic aperture radar SAR; labeled co-occurrence matrix LCM; grey level co-occurrence matrix GLCM; semivariogram; built-up area; remote sensing; fuzzy sets synthetic aperture radar SAR; labeled co-occurrence matrix LCM; grey level co-occurrence matrix GLCM; semivariogram; built-up area; remote sensing; fuzzy sets





Author: Na Li 1,* , Lorenzo Bruzzone 2, Zengping Chen 1 and Fang Liu 1

Source: http://mdpi.com/



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