Change Detection Method for High Resolution Remote Sensing Image in Association with Textural and Spectral Information
WANG Dong-guang1, XIAO Peng-feng1, SONG Xiao-qun2, WANG Tie-cheng3, CHEN Gang1
1. Department of Geographical Information Science, Nanjing University, Nanjing 210093, China;
2. Land and Resources Information Center of Jiangsu Province, Nanjing 210029, China;
3. Surveying Engineering Institute of Jiangsu Province, Nanjing 210013, China
Abstract：High resolution remote sensing image can provide a lot of spectral and textural information,and both of the two kinds of information can help effectively detect the changed information. However,the traditional methods of change-detection based on medium or low spatial resolution remote sensing images only use the spectral information to extract the changed information,with the ignorance of the textural information. In this paper,both the spectral and textural features are integrated in one change-detection method to extract the changed information from high resolution remote sensing image,and the method is called difference principal component transformation. The advantages of the proposed method can be concluded in two aspects. One is that it will be easy to get the internal changed details in the large changed areas according to textural information,which can compensate for the deficiency of spectral information in high resolution images. The other is that some post-processing procedures such as connecting narrow gaps and filling holes can make the change-detection result more complete. The experimental results show that some changes that are spectrally similar but texturally different can be effectively detected after adding textural information in this change-detection method.
王东广, 肖鹏峰, 宋晓群, 王铁成, 陈刚. 结合纹理信息的高分辨率遥感图像变化检测方法[J]. 国土资源遥感, 2012, 24(4): 76-81.
WANG Dong-guang, XIAO Peng-feng, SONG Xiao-qun, WANG Tie-cheng, CHEN Gang. Change Detection Method for High Resolution Remote Sensing Image in Association with Textural and Spectral Information. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(4): 76-81.
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2012, Vol. 24 
