基于空频域纹理特征的高分辨率遥感图像居民地提取
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摘要
为了解决高分辨率遥感图像中居民地信息因光谱和结构复杂度高造成的提取精度低、速度慢等问题。提出一种基于空频域纹理特征的高分辨率遥感图像居民地提取算法,该算法首先对高分辨率居民地图像分别进行特定方向Gabor滤波和分形维数的计算,然后依据得到的空频域纹理图像的局部纹理灰度特征对居民地信息进行提取,最后对提取初步结果进行形态学优化得到最终的提取结果。实验结果表明,该算法对乡村地区和山区居民地信息提取的总体精度达到97%以上,与传统的分形维数方法和Gabor滤波方法相比,误提率降低了45%以上。实现了全自动、有效的提取平原、山区两种地貌的居民地信息。
In order to solve the problem of low accuracy and speed in extracting residential area information from high-resolution remote sensing images,an extraction method based on spatial and frequency texture features is proposed. Firstly,images were subjected separately to fractal dimension computation and specific direction Gabor filtering to obtain both spatial and frequency texture features. Then,residential area information was extracted according to the local gray-scale features of the two texture features. Finally,the extraction results were morphologically optimized. The experimental results show that the Kappa Coefficient of the proposed algorithm reach up to 0. 97.Compared to the traditional fractal dimension and Gabor filtering methods,the Commission Error of the proposed algorithm is reduced by more than 45%. The proposed method achieves automatic and effective extraction of residential area information in both rural region and mountainous region.
In order to solve the problem of low accuracy and speed in extracting residential area information from high-resolution remote sensing images,an extraction method based on spatial and frequency texture features is proposed. Firstly,images were subjected separately to fractal dimension computation and specific direction Gabor filtering to obtain both spatial and frequency texture features. Then,residential area information was extracted according to the local gray-scale features of the two texture features. Finally,the extraction results were morphologically optimized. The experimental results show that the Kappa Coefficient of the proposed algorithm reach up to 0. 97.Compared to the traditional fractal dimension and Gabor filtering methods,the Commission Error of the proposed algorithm is reduced by more than 45%. The proposed method achieves automatic and effective extraction of residential area information in both rural region and mountainous region.
引文
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12 Pentland A P. Fractal-based description of natural scenes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1984,6(6):661-674
13 Ziabari M,Mottaghitalab V,Haghi A K. Distance transform algorithm for measuring nanofiber diameter[J]. Korean Journal of Chemical Engineering,2008,25(4):905-918
14 Daugman J. Uncertainty relation for resolution in space,spatial frequency and orientation optimized by two-dimensional visual cortical filter[J]. Journal of the Optical Society of America,1985,2(7):1160-1169
15 白照广.高分一号卫星的技术特点[J].中国航天,2013(8):5-9Bai Zhaoguang. Technical characteristics of GF-1[J]. Aerospace China,2013(8):5-9
16 陈洪,陶超,邹峥嵘,等.一种新的高分辨率遥感影像城区提取方法[J].武汉大学学报(信息科学版),2013,38(9):1063-1067Chen Hong,Tao Chao,Zou Zhengrong,et al. Automatic urban area extraction using a gabor filter and high-resolution remote sensing imagery[J]. Geomatics and Information Science of Wuhan University,2013,38(9):1063-1067
2 Dutta S,Datta A,Chakladar N D,et al. Detection of tool condition from the turned surface images using an accurate grey level co-occurrence technique[J]. Precision Engineering,2012,36(3):458-466
3 Nyoungui A N,Tonye E,Akono A. Evaluation of speckle filtering and texture analysis methods for land cover classification from SAR images[J]. International Journal of Remote Sensing,2002,23(9):1895-1925
4 Rajesh K,Jawahar C V,Sengupta S,et al. Performance analysis of textural features for characterization and classification of SAR images[J]. International Journal of Remote Sensing,2001,22(8):1555-1569
5 孙宇章,黄璐琦,郭兰萍,等.遥感技术在中药资源调查中的应用[J].中国现代中药,2006,8(9):7-10Sun Yuzhang,Huang Luqi,Guo Lanping,et al. Application of remote sensing technology in investigation of traditional Chinese medicine resources[J]. Modern Chinese Medicine,2006,8(9):7-10
6 Umaselvi M,Kumar S,Athithya M. Color and wavelet based identification of urban and agricultural area using texture features in satellite images[C]//The Proceedings of 2013 IEEE International Conference on Green High Performance Computing. Piscataway:IEEE Press,2013:1-4
7 Li L,Ying Z,Yang T. Facial expression recognition by fusion of Gabor texture features and local phase quantization[C]//The Proceedings of 12th International Conference on Signal Processing(ICSP).Piscataway:IEEE Press,2014:1781-1784
8 潘旭冉,杨帆,杨宜菩,等.基于纹理方向和角点的居民地信息提取[J].科学技术与工程,2017,17(31):120-127Pan Xuran,Yang Fan,Yang Yipu,et al. Information extraction of residential area based on texture directions and corner points[J]. Science Technology and Engineering,2017,17(31):120-127
9 Wang M. Influence of number of features on texture cased residential area extraction from remotely sensed imagery image and signal processing[C]//The Proceedings of 2009 2nd International Congress on Image and Signal Processing. Piscataway:IEEE Press,2009:1-4
10 Riaz F,Hassan A,Rehman S,et al. Texture classification using rotation and scale-invariant Gabor texture features[J]. IEEE Signal Processing Letters,2013,20(6):607-610
11 Mandelbrot B B. How long is the coast of Britain? Statistical selfsimilarity and fractional dimension[J]. Science, 1967, 156(3775):636-638
12 Pentland A P. Fractal-based description of natural scenes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,1984,6(6):661-674
13 Ziabari M,Mottaghitalab V,Haghi A K. Distance transform algorithm for measuring nanofiber diameter[J]. Korean Journal of Chemical Engineering,2008,25(4):905-918
14 Daugman J. Uncertainty relation for resolution in space,spatial frequency and orientation optimized by two-dimensional visual cortical filter[J]. Journal of the Optical Society of America,1985,2(7):1160-1169
15 白照广.高分一号卫星的技术特点[J].中国航天,2013(8):5-9Bai Zhaoguang. Technical characteristics of GF-1[J]. Aerospace China,2013(8):5-9
16 陈洪,陶超,邹峥嵘,等.一种新的高分辨率遥感影像城区提取方法[J].武汉大学学报(信息科学版),2013,38(9):1063-1067Chen Hong,Tao Chao,Zou Zhengrong,et al. Automatic urban area extraction using a gabor filter and high-resolution remote sensing imagery[J]. Geomatics and Information Science of Wuhan University,2013,38(9):1063-1067