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Remote sensing data have been commonly used for agricultural crop monitoring. This paper was assessed the quality of using SAR and optical data fusion for maize classification. Two different SAR data sets from different sensors including dual polarization (HH and VV) X-band COSMO-SkyMed (CSK) and quad polarization (HH, HV, VH and VV) C-band RADARSAT-2 images were fused with THAICHOTE (namely, THEOS,...
Study of the land cover classification using multi-source data are very important for eco-environment monitoring, land use planning and climatic change detection. In this study, the utility of multi-source RADARSAT-2 and LANDSAT-8 multi-spectral images for improving land cover classification performance using Support Vector Machine (SVM) classifier. HH polarized C band RADARSAT-2 images were fused...
According to the ‘salt and pepper’ effect of pixel-based multi-feature classification and over-smoothing of ground details of object-based image analysis, in this paper, an approach, which fuses pixel-based features and multi-scale object-based features is proposed to improve the accuracy of image classification. (1) Firstly, mean shift algorithm is used to segment the image to obtain over-segmentation...
Based on the object-oriented method, this paper presents a new regional shape index (RSI). RSI is a regional feature which measures the gray similarity distance within region in every direction. Firstly, the original image is segmented to obtain small regions. Then the center in each region is calculated, and the distance is calculated from the center of each region within image to boundary of each...
An improved reconstruction algorithm is proposed for compact polarimetric (CP) synthetic aperture radar (SAR) on oil spill detection. Based on the differences in statistical behavior between open and oil-covered sea surfaces, the proposed algorithm can iteratively reconstruct quad-pol SAR images from CP SAR data. During the experiment, it outperformed two existing compact SAR reconstruction algorithms...
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