SAR IMAGE MATCHING IMPROVEMENT USING IMAGE TEXTURE ANALYSIS

被引：0

作者：

Ghannadi, Mohammad Amin ^{[1
]}

Saadatseresht, Mohammad ^{[1
]}

Hasanlou, Mahdi ^{[1
]}

机构：

[1] Univ Tehran, Sch Surveying & Geospatial Engn, Coll Engn, Tehran, Iran

来源：

IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2018年

关键词：

SAR image matching; textural feature; GLCM; optical flow; RADARSAT-2; SIFT;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Matching in high-resolution synthetic aperture radar (SAR) images while being more complicated compared to optical images, is especially important due to its numerous applications. The main aim of current research is to determine improvement of SAR image matching process by deploying texture analysis using gray level's co-occurrence matrix (GLCM). Three parts of the pair of TerraSAR-X images are used to implement the methodology. The results show that for some areas with low texture, the conventional image matching algorithm is not able to detect corresponding points, while using other textural features in image matching process leads to improvement in quantity of acceptable matched points.

引用

页码：6832 / 6835

页数：4

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