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In this letter, a simple, yet very powerful local descriptor called local pattern descriptor (LPD) is proposed for synthetic aperture radar (SAR) images classification. The descriptor aims at exploiting the underlying properties of SAR image texture. Specifically, LPD consists of two parts: image quantization and statistical features extraction. The method of image quantization is based on recent...
In this paper, we propose a theoretically new and effective feature for SAR image classification. The new feature combines traditional gray level co-occurrence matrix (GLCM) textural feature and the recent multilevel local pattern histogram (MLPH) feature. It can not only describe intrinsic property of land-cover/land-use surfaces, corresponding to textural information, but it also captures both local...
Since superpixel takes spatial relationship between pixels into account, which makes the image classification process more understandable and the results more satisfactory, superpixel-based classification methods have been widely studied in recent years. However, due to speckle noise, traditional superpixel generating algorithms still have some drawbacks for synthetic aperture radar (SAR) image. In...
Aiming at the classification problem of Synthetic aperture radar (SAR) images, a classifier based on image intensity and structure is constructed. To overcome the disadvantages of conventional template matching algorithms, similarity between two images is calculated by Hausdorff function, which can handle the distortions and pixel perturbations. The function is then fed into Support vector machines...
The present paper deals with the land cover classification of high resolution IKONOS images using multi-feature fusion, which is the traditional optical features analysis combined with texture feature analysis. The study area covers the residential region of the urbanized environment of Beijing, China. Different optical features including grey data in different layers and texture features contains...
Classification and extraction of geospatial features from high spatial resolution imageries approved is one of the most significant steps for spatial database acquisition and updating in GIS. This research is to explore the methodologies of recognizing shape and elevation characteristics of spatial features on the remote sensed images. We focus on the road network classification and extraction among...
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