作者：
A. ToumiA. KhenchafE3I2-EA3876
ENSIETA-Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d''Armement Brest France
We describe in this paper, data processing algorithms applied on radar image in order to extract feature descriptors and then to perform recognition task. Several kinds of descriptors can be used to acquire informatio...
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We describe in this paper, data processing algorithms applied on radar image in order to extract feature descriptors and then to perform recognition task. Several kinds of descriptors can be used to acquire information about target characteristics from radar images such as ISAR (Inverse Synthetic Aperture Radar) images. This paper presents two types of vector descriptors extracted via two minds of transformed images so-called polar and log-polar images obtained respectively from the polar and log-polar mapping. In order to guarantee the invariance of some geometrical transformation, additional processing are proposed. In this paper, we present the polar and log-polar transformations and then the classification scheme adapted on correspondent polar and log-polar templates. In the classification step, log-polar and polar mapping results are compared using adapted classification scheme.
Object recognition is challenging problem in computer vision due to appearance variation and presence of visual clutter and occlusions. Recently manifolds are thought to be fundamental for visual perception, and manif...
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Object recognition is challenging problem in computer vision due to appearance variation and presence of visual clutter and occlusions. Recently manifolds are thought to be fundamental for visual perception, and manifold learning algorithms are developed for discovering intrinsical features. Selective visual attention mechanism provides tools to reduce computation cost and avoid the influence of clutter background. In this paper, we described a new object recognition method, the submanifold distance (SMD) algorithm, which is induced by the visual attention mechanism to provide complex object recognition. Experiments with airport remotesensingimages illustrated that our proposed algorithm can recognize complex objects accurately, robustly and quickly.
Sparse representation using the over-complete dictionary makes that decomposition coefficients are more sparse, and can reflect the inherent characteristics and structure of signals. A novel fusion method based on IHS...
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Soil organic matter (SOM) is an essential and dynamic variable in terrestrial ecosystem. This study used a method for mapping its spatial distribution by remotesensing technique. An image observed by Landsat 5 was us...
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Soil organic matter (SOM) is an essential and dynamic variable in terrestrial ecosystem. This study used a method for mapping its spatial distribution by remotesensing technique. An image observed by Landsat 5 was used to estimate the spatial pattern of surface SOM in a town scale. The results showed that the concentration of surface SOM in study Jianshe town had a negative correlation (r =0.51, P2=0.61, P
image segmentation is very essential and critical to imageprocessing and patternrecognition. Watershed is the most popular one among all the proposed image segmentation algoritbms, but it suffers from over-segm...
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image segmentation is very essential and critical to imageprocessing and patternrecognition. Watershed is the most popular one among all the proposed image segmentation algoritbms, but it suffers from over-segmentation. To resolve the over-segmentation problem and obtain a concise region representation has been the focus of many researchers. There are many ways to reduce the over-segmentation However, Human visual system (HVS) is often not incorporated into the consideration and process of *** paper presents a new approach to high resolution remotesensingimage segmentation taking into consideration human visual system (HVS) model. A Contrast Sensitivity Function (CSF) based filtering is applied to the image before watershed trAnsform. Multi-scale spatial frequency filtering images are derived from setting multi-scale viewing distance. Then the region merging based on Just Noticeable Difference (JND) is applied to the segmentation results. Finally, the efffect of reducing over segmentation based on CSF and JND is analyzed and significant improvement is reported in the experimental results.
In the field of crop identification with remotesensing technology, current multi-temporal methods usually do not made full use of target crop's temporal features and spectral features. An improved multi-temporal ...
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ISBN:
(纸本)9781424458561
In the field of crop identification with remotesensing technology, current multi-temporal methods usually do not made full use of target crop's temporal features and spectral features. An improved multi-temporal masking classification method was proposed for winter wheat identification in Jiaodong Peninsula. The improved method using four temporal MODIS NDVI product images and two temporal TM surface reflectance imagines could better conduct both temporal feature recognition and spectral feature recognition. First, a winter wheat mask was generated from four proper temporal MODIS NDVI product images to distinguish winter wheat from the other local crops;second, the winter wheat mask was applied to a multi-time phases combined TM image. Then according to classes' spectral separability, a set of TM bands were selected to form spectral space for classification, and winter wheat was identified by spectral classification in the TM spectral space. In the study area, the identification accuracy reaches 94.92%. The results indicate that the appropriate winter wheat mask design and spectral classification bands selection could help the improved multitemporal method to get high winter wheat identification accuracy.
Light Detection and Ranging (LiDAR) has become a valuable data source for urban data acquisition. This paper gives an overview about current trends in the automation of object extraction from LiDAR data. These trends ...
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Light Detection and Ranging (LiDAR) has become a valuable data source for urban data acquisition. This paper gives an overview about current trends in the automation of object extraction from LiDAR data. These trends are caused by the technical development of LiDAR sensors that enable the acquisition of point clouds at higher resolution as well as the recording of the full waveform of the returned signal, and by the adoption of processing techniques from the Computer Vision and patternrecognition communities. Triggered by these developments, new applications are being found for LiDAR data.
Landscape pattern analysis is becoming the core to study global or local change. Incorporated with fast, dynamic and precise spatial information technology, Landscape pattern analysis has been a foundation for the gov...
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Landscape pattern analysis is becoming the core to study global or local change. Incorporated with fast, dynamic and precise spatial information technology, Landscape pattern analysis has been a foundation for the governments to make decision. In this paper, the authors do the landscape classification on TM/ETM in Maoxian county firstly, then study the change influence of national policies on the landscape pattern of Maoxian county. The result indicates that with the polices changes, the landscape pattern in Maoxian county was changed accordingly.
Most Earth observation satellites provide both panchromatic images with a higher spatial resolution and multispectral images with a lower spatial resolution. image fusion techniques can integrate the spatial detail of...
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Most Earth observation satellites provide both panchromatic images with a higher spatial resolution and multispectral images with a lower spatial resolution. image fusion techniques can integrate the spatial detail of the panchromatic image and the spectral characteristics of the multispectral image into one image Exiting image fusion techniques such as the Intensity-Hue-Saturation (IHS) transform method, Brovey transform method and High Pass Filter (HPF) method may not be optimization while fusing the new generation commercial satellite image such as ALOS. The most serious problem is that the fused image usually has a notable deviation in visual appearance and spectral values from the original image. In this paper, we proposed a new fusion method for ALOS images, when adding the detail information of panchromatic image to the intensity component of multispectral image, the weight coefficients are determined adaptively based on the structural similarity(SSIM) between the panchromatic image and the intensity component of the multispectral image. Experimental results indicate that this method is effective when fusing ALOS image.
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