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In this paper, we present a new unsupervised classification method based on a novel polarization feature, which reflects the proportion of co-polarization component and cross-polarization component of scatters in PolSAR image. We combine this novel polarization feature with backscattering power and scattering power entropy to perform the initial classification. Then apply a merge criterion to merge...
This paper presents a new method for polarimetric synthetic aperture radar (PolSAR) image classification. Firstly, to get a reasonable edge strength map, polarimetric information is used in edge strength calculation, and watershed algorithm is used to obtain the oversegmentation using the edge strength. Secondly, a searching table is used to determine the most suitable region to be merged. Finally,...
Recently a few works of semi-supervised learning methods based on graph have been proposed for remote sensing. The common idea of these methods are that they build a graph using the samples of the image. Most of their time complexity is relatively large, and they ignore the spatial information of the image, which leads to unsatisfactory classification results. this paper proposes a novel semi-supervised...
A novel polarimetric synthetic aperture radar (PolSAR) image classification method based on Deep Belief Networks (DBNs) is proposed in this paper. First, the coherency matrix data are converted to a 9-dimentional data. Second, many patches are randomly selected from each dimension in the 9-dimentional data, and many filters can be obtained from a Restricted Boltzmann Machine (RBM) trained by using...
In conventional terrain classification for the polarimetric SAR (POLSAR) images, color features are rarely involved unless in one recent supervised work. Unlike that work, the color features are exploited for the unsupervised classification in this paper. Firstly, based on the polarimetric decomposition of the POLSAR data, the common color spaces, such as RGB, HSI, and CIELab are calculated. The color...
How to use the POLSAR data to classify and interpret the conditions of the earth is a very important research field of POLSAR. In this paper, we propose an improved algorithm on the basis of studying and analyzing some common algorithms. This technique introduces the fisher criterion in the feature selection and the hierarchical method in the classification of POLSAR image, which can improve Lee's...
SAR image retrieval, lacking of well performance recently due to the particularity of SAR image, has drawn more and more attention with the increasing volume of SAR data and the dramatically enlarging application range of SAR image. This paper considers both the characteristic of content-based image retrieval (CBIR) and SAR image, proposing a novel SAR image retrieval method. The proposed method can...
This paper presents an effective algorithm of palmprint feature extraction. This algorithm is constructed on the basis of Gabor filter and moment invariant (MI). The process of implementing the algorithm is as follows: first, we perform wavelet transform of the original region of interest (ROI) of the palmprint image to get the approximation image (AIROI). Later, we exploit the Gabor filter to capture...
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