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为了进一步提高遥感图像建筑物区域的识别精度,提出了一种基于中值稳健扩展局部二值模式(median robust extended local binary pattern,MRELBP)、Franklin矩和布谷鸟优化支持向量机(support vector machine,SVM)的分类方法。首先,通过MRELBP特征算子计算图像块的纹理特征向量,并根据Franklin矩得到形状特征向量,组合图...
Chinese HY-1C/1D satellites will use a 5nm/10nm-resolutional visible-near infrared(VNIR) hyperspectral sensor with the solar calibrator to cross-calibrate with other sensors. The hyperspectral radianc...
This paper presents a method which combines the traditional threshold method and SVM method, to detect the cloud of Landsat-8 images. The proposed method is implemented using DSP for real-time cloud d...
This study demonstrates the application of CIELAB, Color intensity, and One Dimensional Scalar Constancy as features for image recognition and classifying benthic habitats in an image with the coastal...
The common method of LiDAR classifications is Markov random fields (MRF). Based on construction of MRF energy function, spectral and directional features are extracted for on-board urban point clouds....
Scene matching is the process of locating a region of an image with the corresponding region of another image where both image regions represent the same scene. Although a lot of algorithms have appea...
The number of image features used by content-based remote sensing image retrieval (CBRSIR) system is not less than one hundred, and the image amount is very large, at the same time, the time cost is v...
Soil Desertification has severely threatened inner stability and sustainable development in arid areas, so extracting soil desertification information based on remote sensing and mastering its spatial...
Automatic image categorization using low-level features is a challenging research topic in remote sensing application. In this paper, we formulate the image categorization problem as an image texture ...
The method of constructing navigation star catalogue always based on Magnitude Filtering Method (MFM). But it did not work well because of two typical disadvantages. On one side it would extract so ma...
We present a new object-oriented land cover classification method based on Support Vector Machine (SVM) by fusing spectral and textural information of High-Resolution (HR) aerial imagery and Digital...
The use of satellite imagery in the derivation of land cover information has yielded immense dividends to numerous application fields such as environmental monitoring and modeling, map making and rev...
In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imagerie...
The increase of population and economic development, especial the land use and urbanization bring the wetland resource a huge pressure and a serious consequence of a sharp drop in the recent years. ...
As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture...

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