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This paper presents a novel shadow detection method in remote sensing images based on edge feature description of candidate regions. Edge gradient ratio is defined and used to represent the inherent properties of shadow regions. To improve the detection result, weighted edge gradient ratio (WEGR) is addressed, where the weight of a region is determined by the number of pixels belonging to shadow in...
Most studies showed that most hyperspectral image classification encountered the Hughes phenomenon due to the redundant features, especially in the small sample size problem. Feature extraction method such as linear discriminant analysis (LDA), nonparametric weighted feature extraction (NWFE) is a preprocessing step before classification and used to combine and reduce the original features into a...
The band selection of multispectral remote sensing image is a key issue and hot topic in remote sensing image processing domain. Considering that the band selection results of methods are usually not satisfying, a novel remote sensing image band selection method based on independent component analysis is proposed in this paper. The proposed method determine the number of independent components according...
Due to the variations in the terrain, illumination and scale, it is difficult to detect craters from remote sensing image of planet surface. This paper proposes a novel automatic crater detection method by introducing the local non-negative matrix factorization (LNMF) for remote sensing images of Martian surface. LNMF is aimed at learning localized, part-based features from global samples, which has...
The paper addresses built up information extraction from high resolution imagery from two satellites, ZY-1 02C and SPOT-5. The testing is part of a larger experiment that explores spectral, textural and morphological satellite image properties aiming to extract built up information for global built up mapping and characterization. In this work we test SPOT-5 and ZY-1 02C satellites for textural properties...
The paper presents an approach for building damage detection from high resolution remote sensing image using multi-feature analysis and the fuzzy reasoning procedure. The selected area of our study is in Yushu, which was strongly hit by 7.1-magnitude earthquake. The study area contains 101 buildings, of which 46 are collapsed and 55 are un-collapsed. First, the buildings were selected one-by-one from...
Road is a kind of very typical artificial object. Road extraction from multi-scale remote sensing images is significant both in military field and in people's daily lives. With the development of remote sensing technology, the scale of remote sensing images that can be obtained becomes various. Therefore, the research of multi-scale remote sensing images is getting more and more attention and it is...
In this paper, we develop an automatic method for counting palm trees in UAV images. First we extract a set of keypoints using the Scale Invariant Feature Transform (SIFT). Then, we analyze these keypoints with an Extreme Learning Machine (ELM) classifier a priori trained on a set of palm and no-palm keypoints. As output, the ELM classifier will mark each detected palm tree by several keypoints. Then,...
The Tasseled Cap Transformation (TCT) has been widely used in the remote sensing community. However, TCT is sensor dependent, so a new sensor requires a reworking of the TCT starting with analysis of data structure of images. The purpose of this paper is to derive the TCT parameters for the Landsat 8 OLI TOA Reflectance images, and compare the differences between the Tasseled Cap Transformation parameters...
In this paper, classification via joint sparse representation of the monogenic signal is presented for target recognition in SAR imagery. First, the monogenic signal is performed to capture the characteristics of SAR image. Since it is infeasible to directly apply the raw component to classification due to the high data dimension and redundancy, three augmented feature vectors are defined via uniform...
In this paper, we introduce the first analysis of ship detection performance using simulated RADARSAT Constellation Mission (RCM) data in the Ship Detection, Low and Medium Resolution modes. The ship detection performance is assessed for a number of linear and compact polarimetric (CP) dual-polarimetric (dual-pol) systems data simulated from RADARSAT-2 Fine quad mode in the three RCM modes. The impact...
Synthetic Aperture Radar images is a proven technology that can be used to detect ships at sea which have no active transponders (commonly referred to as dark targets). Various methods have been proposed that process SAR images to monitor these targets. In this paper, we propose a novel ship detection method for Advanced Synthetic Aperture Radar imagery that combines a Constant False Alarm Rate ship...
Synthetic Aperture Radar images are able to detect ships that would be hidden to tradition ship tracking methods due to their transponders being turned off. Using a SAR image as input, the CFAR method can highlight these ships given a correctly chosen threshold value. Typically, the threshold value is chosen as a single floating value for all positions creating a flat threshold plane. This study introduces...
Satellite-borne SAR is used for sea surface observation and extraction of meteo-marine features as well as detection of oil slicks. In this paper we want to describe the activity based on the detection algorithm we developed in previous activities, able to identify oil spills in an automatic routinely way, as well as to evaluate detection reliability with a percentage value. Starting from that previous...
Coal-bed methane (CBM), as an increasingly promising resource for the energy supply, deserves further exploration and accurate reservoir evaluation. It is also required to dynamically monitor the reservoirs (>200 m). Remote sensing methods in regular wavebands may fail in the depth sounding, with only imaging geo-objects shallower than 100 m. In contrast, the Super-Low Frequency (SLF) remote sensing...
The general process of oil spill detection from SAR image with artificial neural network (ANN) classifier briefly includes five steps, target extraction, feature extraction, feature selection, ANN training and ANN classification. Feature extraction and feature selection are concerned in this paper. Firstly, 68 features are calculated for each target. By cross-correlation analysis, 24 features are...
As having the imaging ability of area in front of flight direction, forward-looking synthetic aperture radar (SAR) has become a hot topic in areas of SAR research. Nevertheless, the currently exploited imaging algorithms of forward-looking SAR suffer from poor azimuth resolution induced by limited azimuth aperture length. To address this challenge, we develop a super-resolving imaging algorithm for...
The displaced phase centre multiple azimuth beams (DPC-MAB) synthetic aperture radar (SAR) can realize wide swath imaging with high azimuth resolution, but it has strict requirement on the pulse repetition frequency (PRF). When actual PRF deviates from the ideal PRF, non-uniform azimuth sampling will arise and then seriously interfere with SAR imaging. This paper proposes a novel reconstruction method...
As the need for radar applications has become more urgent, conventional radar performance does not meet the current demand for observation. In recent years, the MIMO radar is considered to have great potential. MIMO SAR can get more phase center for imaging, interference, GMTI, or any other application. Waveform design is the key point of MIMO SAR, and it's also the current biggest bottlenecks of...
A cooperation earth observation model constituted by two SAR satellites and one optical remote sensing satellite is proposed. In this model, the optical remote sensing satellite orbit plane locates in the middle of two SAR satellites, and two SAR satellites observe the same ground area from two sides of the optical satellite respectively. However, because of the influence of earth curvature, not only...
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