Texture Measurement Through Local Pattern Quantization for SAR Image Classification

被引：2

作者：

Chakraborty, Debasish ^{[1
]}

Dutta, Dibyendu ^{[1
]}

Sharma, Jaswant Raj ^{[2
]}

机构：

[1] ISRO, RRSC East NRSC, Kolkata 700156, India

[2] ISRO, Reg Ctr NRSC, Hyderabad 500037, Andhra Pradesh, India

来源：

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING | 2016年 / 44卷 / 03期

关键词：

Image; Texture; Pattern; SAR; Classification; RISAT-1; RISAT-2; Local pattern quantization; SEGMENTATION; AREAS;

D O I：

10.1007/s12524-015-0495-8

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

A novel local pattern based classification algorithm for SAR image is proposed in this paper. The proposed method initially quantizes homogeneous and non-homogeneous patterns within the moving window. An operator is constructed to quantize local patterns. Quantized patterns are then used for measuring texture around the central pixel within the moving window. The ISODATA algorithm is used to classify texture transformed image. The proposed classification method is robust to speckle noise, computationally simple and does not need to set any predefined parameter for classification. The validation of the method is done on RISAT-1 and RISAT-2 data.

引用

页码：471 / 477

页数：7

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