Efficient Combination of Texture and Color Features in a New Spectral Clustering Method for PolSAR Image Segmentation
In this paper, an efficient combination of texture and color features is proposed for polarimetric synthetic aperture radar (PolSAR) image segmentation. In proposed method, the PolSAR image is first segmented using the mean-shift method. Then, in each segment obtained from the mean shift, the first...
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| Veröffentlicht in: | National Academy science letters 2017-04, Vol.40 (2), p.117-120 |
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| creator | Akbarizadeh, Gholamreza Rahmani, Masoumeh |
| description | In this paper, an efficient combination of texture and color features is proposed for polarimetric synthetic aperture radar (PolSAR) image segmentation. In proposed method, the PolSAR image is first segmented using the mean-shift method. Then, in each segment obtained from the mean shift, the first moment of color for the three color components of L* a* b* color space is obtained. On the other hand, a texture feature vector for each pixel of the image is formed corresponding to the texture edge energy at different directions with Gabor filter. Then, a new spectral clustering method is used to combine texture and color features. The results show that the proposed method is effective in PolSAR image segmentation. |
| doi_str_mv | 10.1007/s40009-016-0513-6 |
| format | Article |
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In proposed method, the PolSAR image is first segmented using the mean-shift method. Then, in each segment obtained from the mean shift, the first moment of color for the three color components of L* a* b* color space is obtained. On the other hand, a texture feature vector for each pixel of the image is formed corresponding to the texture edge energy at different directions with Gabor filter. Then, a new spectral clustering method is used to combine texture and color features. 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Acad. Sci. Lett</addtitle><description>In this paper, an efficient combination of texture and color features is proposed for polarimetric synthetic aperture radar (PolSAR) image segmentation. In proposed method, the PolSAR image is first segmented using the mean-shift method. Then, in each segment obtained from the mean shift, the first moment of color for the three color components of L* a* b* color space is obtained. On the other hand, a texture feature vector for each pixel of the image is formed corresponding to the texture edge energy at different directions with Gabor filter. Then, a new spectral clustering method is used to combine texture and color features. 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Acad. Sci. Lett</stitle><date>2017-04-01</date><risdate>2017</risdate><volume>40</volume><issue>2</issue><spage>117</spage><epage>120</epage><pages>117-120</pages><issn>0250-541X</issn><eissn>2250-1754</eissn><abstract>In this paper, an efficient combination of texture and color features is proposed for polarimetric synthetic aperture radar (PolSAR) image segmentation. In proposed method, the PolSAR image is first segmented using the mean-shift method. Then, in each segment obtained from the mean shift, the first moment of color for the three color components of L* a* b* color space is obtained. On the other hand, a texture feature vector for each pixel of the image is formed corresponding to the texture edge energy at different directions with Gabor filter. Then, a new spectral clustering method is used to combine texture and color features. 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| source | Springer Nature - Complete Springer Journals |
| subjects | Color History of Science Humanities and Social Sciences Image processing Image segmentation multidisciplinary Science Science (multidisciplinary) Short Communication |
| title | Efficient Combination of Texture and Color Features in a New Spectral Clustering Method for PolSAR Image Segmentation |
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