SAR Image Segmentation Based on Multiresolution GLCP in Overcomplete Brushlet Domain

Author

Li, Jumei ; Zhong, Hua ; Jiao, Licheng

Author_Institution

Inst. of Intelligent Inf. Process., Xidian Univ., Xi´´an

fYear

2006

fDate

16-19 Oct. 2006

Firstpage

1

Lastpage

4

Abstract

Based on the multi-scale direction characteristics of overcomplete brushlet transform, a feature extraction method called multiresolution grey level co-occurrence probabilities (GLCP) in overcomplete brushlet domain is presented, which makes full use of the direction information in different subbands. The segmentation results of Brodatz mosaics and synthetic aperture radar (SAR) image show that the proposed feature extraction method outperforms other methods such as brushlet, GLCP and DWT in the segmentation accuracy on the synthetic mosaic and synthetic aperture radar (SAR) image

Keywords

feature extraction; image resolution; image segmentation; probability; radar imaging; radar resolution; synthetic aperture radar; Brodatz mosaics; SAR image segmentation; feature extraction method; grey level cooccurrence probability; multiresolution GLCP; overcomplete brushlet transform; synthetic aperture radar; Feature extraction; Fourier transforms; Frequency; Image analysis; Image resolution; Image segmentation; Image texture analysis; Spatial resolution; Synthetic aperture radar; Wavelet analysis; feature extraction; image segmentation; multiresolution GLCP; overcomplete brushlet;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2006. CIE '06. International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-9582-4

Electronic_ISBN

0-7803-9583-2

Type

conf

DOI

10.1109/ICR.2006.343369

Filename

4148444