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Classification of Very High Spatial Resolution Imagery Based on a New Pixel Shape Feature Set

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5 Author(s)
Hua Zhang ; Key Lab. for Land Environ. & Disaster Monitoring of State Bur. of Surveying & Mapping (SBSM), China Univ. of Min. & Technol., Xuzhou, China ; Wenzhong Shi ; Yunjia Wang ; Ming Hao
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This letter presents a novel spatial features extraction method for the high spatial resolution multispectral imagery (HSRMI) classification. First, Canny filter algorithm is applied to extract the edge information to obtain the fuzzy edge map. Secondly, adaptive threshold value for each pixel's homogeneous region (PHR) calculation is determined based on the fuzzy edge map and original image. Next, the PHR for every pixel is obtained based on the fuzzy edge map, adaptive threshold value and original image. And then, the pixel shape feature set (PSFS) is extracted based on the PHR. Lastly, SVM classifier is applied to classify the hybrid spectral and PSFS. Two different experiments were performed to evaluate the performance of PSFS, in comparison with spectral, gray level co-occurrence matrix (GLCM) and the existing pixel shape index (PSI). Experimental results indicate that the PSFS achieved the highest accuracy, hence, providing an effective spectral-spatial classification method for the HSRMI.

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Geoscience and Remote Sensing Letters, IEEE  (Volume:11 ,  Issue: 5 )