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Efficient Combination of Texture and Color Features in a New Spectral Clustering Method for PolSAR Image Segmentation

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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. The results show that the proposed method is effective in PolSAR image segmentation.

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Acknowledgments

This work was supported by the Shahid Chamran University of Ahvaz, Ahvaz, Iran, as an M.Sc. thesis under Grant number 94/3/02/31579.

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Authors and Affiliations

  1. Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

    Gholamreza Akbarizadeh & Masoumeh Rahmani

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  1. Gholamreza Akbarizadeh
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  2. Masoumeh Rahmani
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Correspondence to Gholamreza Akbarizadeh.

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Akbarizadeh, G., Rahmani, M. Efficient Combination of Texture and Color Features in a New Spectral Clustering Method for PolSAR Image Segmentation. Natl. Acad. Sci. Lett. 40, 117–120 (2017). https://doi.org/10.1007/s40009-016-0513-6

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  • DOI: https://doi.org/10.1007/s40009-016-0513-6

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