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Urban building density has always being an important indicator for city planning, land management and resident density evaluation. Recently, very high resolution (VHR) Synthetic Aperture Radar (SAR) sensors, delivering images with metric or sub-metric resolution, make it possible to extract urban fabric (like urban building density) with SAR imagery. In this article, we propose a highly efficient...
In this paper, an improved GVF snake model that allows controllable snakes is proposed. Two kinds of extern constraint forces are exploited in the model. The first one can pin specified points on the snake and determine the basic shape of a snake. The second one avoids generating ears during curve evolution. It ensures that the curves are smooth and won't grow in a wrong direction. The improved snakes...
This paper presents an evaluation of different features for polarimetric SAR (PolSAR) image classification. Firstly, we select several of the polarimetric features to give a summary on them. Then we give an insight into their classification performance together with a texture feature using the support vector machine (SVM). Finally, we employ a feature combination and selection strategy that optimizes...
In this paper, we propose a new method for unsupervised classification of polarimetric synthetic aperture radar interferometry (PolInSAR) images based on Shannon Entropy Characterization. Firstly, we use polarimetric H (entropy) and a parameters to classify the image initially. Then, we reclassify the image according to the span of Shannon Entropy Characterization. Finally, we fuse the results of...
In this paper, we present a study of extracting urban areas from Polarimetric Synthetic Aperture Radar (PolSAR) images using only positive samples. We solve this problem by learning a standard binary classifier (urban/non-urban) given an incomplete set of positive samples (urban) and a set of unlabeled samples (some of which are urban and some of which are non-urban) based on the work of Elkan and...
This paper describes a framework for multi-scale gray level analysis of images. It defines scales based on gray levels and organizes the basic “atoms” with a topographic map. The aim of this approach is to separate a large number of pixels concentrating in a narrow range of gray values. The main advantage of the methodology is that it allows manipulating pixels according to gray levels and spatial...
The paper proposes a fast and accurate semantic segmentation approach for a large Polarimetric SAR (PolSAR) image using Conditional Random Fields (CRFs). It efficiently incorporates the polarimetric signatures, texture and intensity features into a unite CRFs model, and employs a fast max-margin training method for parameters learning. Experiments on RadarSat-2 PolSAR data in Flevoland test site demonstrate...
Flood is one of the most common and expensive natural disaster. Rapid and efficient procedure to accurately detect the flood-inundated area irrespective of weather conditions will help the monitoring and rescuing during the seasonal flooding period. In this paper, a procedure is proposed to obtain the flood mapping using multi-temporal TerraSAR-X data. And a comparative experiment is design to test...
The technique core of grain reserves automatical supervision and audit system which based on video is to identify the grain warehouse scene video, and accurately gets the sum of grain quantity. The key to identifying the quantity is the shape of package, and the key to identifying shape is processing and describing the boundary of package. Based on a lot of research and experiment on the edge detection...
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