Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis
Image texture is an important visual cue in image processing and analysis. Texture feature expression is an important task of geo-objects expression by using a high spatial resolution remote sensing image. Texture features based on gray level co-occurrence matrix (GLCM) are widely used in image spat...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2019/4970376 |
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| _version_ | 1832549873523621888 |
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| author | Min Cao Dongping Ming Lu Xu Ju Fang Lin Liu Xiao Ling Weizhi Ma |
| author_facet | Min Cao Dongping Ming Lu Xu Ju Fang Lin Liu Xiao Ling Weizhi Ma |
| author_sort | Min Cao |
| collection | DOAJ |
| description | Image texture is an important visual cue in image processing and analysis. Texture feature expression is an important task of geo-objects expression by using a high spatial resolution remote sensing image. Texture features based on gray level co-occurrence matrix (GLCM) are widely used in image spatial analysis where the spatial scale is especially of great significance. Based on the Fourier frequency-spectral analysis, this paper proposes an optimal scale selection method for GLCM. Different subset textures are firstly upscaled by GLCM with different window sizes. Then the multiscale texture feature images are converted into the frequency domain by Fourier transform. Consequently, the radial distribution and angular distribution curves changing with different window sizes from spectrum energy can be achieved, by which the texture window size can be selected. In order to verify the validity of this proposed texture scale selection method, this paper uses high-resolution fusion images to classify land cover based on multiscale texture expression. The results show that the proposed method combining frequency-spectral analysis-based texture scale selection can guarantee the quality and accuracy of the classification, which further proves the effectiveness of optimal texture window size selection method bases on frequency spectrum analysis. Other than scale selection in spatial domain, this paper casts a novel idea for texture scale selection in the frequency domain, which is meant for scale processing of remote sensing image. |
| format | Article |
| id | doaj-art-a3f23757311c4892a795e45c2f47c880 |
| institution | Kabale University |
| issn | 2314-4920 2314-4939 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-a3f23757311c4892a795e45c2f47c8802025-02-03T06:08:27ZengWileyJournal of Spectroscopy2314-49202314-49392019-01-01201910.1155/2019/49703764970376Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image AnalysisMin Cao0Dongping Ming1Lu Xu2Ju Fang3Lin Liu4Xiao Ling5Weizhi Ma6School of Information Engineering China University of Geosciences (Beijing), 29 Xueyuan Road, Haidian, Beijing, ChinaSchool of Information Engineering China University of Geosciences (Beijing), 29 Xueyuan Road, Haidian, Beijing, ChinaSchool of Information Engineering China University of Geosciences (Beijing), 29 Xueyuan Road, Haidian, Beijing, ChinaSchool of Information Engineering China University of Geosciences (Beijing), 29 Xueyuan Road, Haidian, Beijing, ChinaSchool of Information Engineering China University of Geosciences (Beijing), 29 Xueyuan Road, Haidian, Beijing, ChinaSchool of Information Engineering China University of Geosciences (Beijing), 29 Xueyuan Road, Haidian, Beijing, ChinaBeijing Yanqing Municipal Commission of Housing and Urban-Rural Development, 89 Dongwai Avenue, Yanqing, Beijing, ChinaImage texture is an important visual cue in image processing and analysis. Texture feature expression is an important task of geo-objects expression by using a high spatial resolution remote sensing image. Texture features based on gray level co-occurrence matrix (GLCM) are widely used in image spatial analysis where the spatial scale is especially of great significance. Based on the Fourier frequency-spectral analysis, this paper proposes an optimal scale selection method for GLCM. Different subset textures are firstly upscaled by GLCM with different window sizes. Then the multiscale texture feature images are converted into the frequency domain by Fourier transform. Consequently, the radial distribution and angular distribution curves changing with different window sizes from spectrum energy can be achieved, by which the texture window size can be selected. In order to verify the validity of this proposed texture scale selection method, this paper uses high-resolution fusion images to classify land cover based on multiscale texture expression. The results show that the proposed method combining frequency-spectral analysis-based texture scale selection can guarantee the quality and accuracy of the classification, which further proves the effectiveness of optimal texture window size selection method bases on frequency spectrum analysis. Other than scale selection in spatial domain, this paper casts a novel idea for texture scale selection in the frequency domain, which is meant for scale processing of remote sensing image.http://dx.doi.org/10.1155/2019/4970376 |
| spellingShingle | Min Cao Dongping Ming Lu Xu Ju Fang Lin Liu Xiao Ling Weizhi Ma Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis Journal of Spectroscopy |
| title | Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis |
| title_full | Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis |
| title_fullStr | Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis |
| title_full_unstemmed | Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis |
| title_short | Frequency Spectrum-Based Optimal Texture Window Size Selection for High Spatial Resolution Remote Sensing Image Analysis |
| title_sort | frequency spectrum based optimal texture window size selection for high spatial resolution remote sensing image analysis |
| url | http://dx.doi.org/10.1155/2019/4970376 |
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