施蓓琦, 刘春, 陈能, 孙伟伟. 利用高光谱遥感影像纹理滤波的城市居民地识别[J]. 武汉大学学报 ( 信息科学版), 2012, 37(8): 915-920.
引用本文: 施蓓琦, 刘春, 陈能, 孙伟伟. 利用高光谱遥感影像纹理滤波的城市居民地识别[J]. 武汉大学学报 ( 信息科学版), 2012, 37(8): 915-920.
SHI Beiqi, LIU Chun, CHEN Neng, SUN Weiwei. Residential Area Recognition Using Texture Filtering from Hyper-spectral Remote Sensing Imagery[J]. Geomatics and Information Science of Wuhan University, 2012, 37(8): 915-920.
Citation: SHI Beiqi, LIU Chun, CHEN Neng, SUN Weiwei. Residential Area Recognition Using Texture Filtering from Hyper-spectral Remote Sensing Imagery[J]. Geomatics and Information Science of Wuhan University, 2012, 37(8): 915-920.

利用高光谱遥感影像纹理滤波的城市居民地识别

Residential Area Recognition Using Texture Filtering from Hyper-spectral Remote Sensing Imagery

  • 摘要: 高光谱影像具有丰富的光谱和空间结构信息,传统的基于光谱特征的分割方法易使分割区域过于细碎,从而降低了居民地信息提取的精度。尝试将纹理信息引入到特征空间,以提高信息识别、提取的精度。纹理信息采用多尺度3D-Gabor滤波器对经过特征选择后的高光谱影像进行滤波,进一步计算纹理能量和纹理特征,然后利用多特征聚类实现图像的初步分割,最终通过形态学方法获取影像中的居民地信息。实验表明,基于3D-Gabor滤波的方法能有效地识别、提取高光谱影像中的居民地信息。

     

    Abstract: Hyper-spectral remote sensing imagery provides a large amount of spectral and structure information.However,these availabilities challenge the traditional spectral segmentation methods which may cause salt and pepper effect and low information extraction accuracy.In order to overcome this disadvantage,texture information is proposed into feature space.A 3D-Gabor filter is used to represent the spectral/spatial properties of hyper-spectral data.Thus multi-scale,multi-oriented texture features are extracted.And feature energy from 3D feature points is projected into subspace with PCA which can represent input data with lower dimensional feature vectors.Then the image segmentation is constructed by k-means clustering.Following these steps,the initial residential areas can be obtained,but with many deficiencies including the existence of holes and useless patches.To resolve these problems,a morphological space based method is used to dissolve these residential patches.The experiment on PHI-3 data demonstrates the utility of the algorithm for residential areas recognition.

     

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