Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform
Spatial images are inevitably mixed with different levels of noise and distortion. The contourlet transform can provide multidimensional sparse representations of images in a discrete domain. Because of its filter structure, the contourlet transform is not translation-invariant. In this paper, we us...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/467412 |
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| _version_ | 1832568301182517248 |
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| author | Pengcheng Han Junping Du |
| author_facet | Pengcheng Han Junping Du |
| author_sort | Pengcheng Han |
| collection | DOAJ |
| description | Spatial images are inevitably mixed with different levels of noise and distortion. The contourlet transform can provide multidimensional sparse representations of images in a discrete domain. Because of its filter structure, the contourlet transform is not translation-invariant. In this paper, we use a nonsubsampled pyramid structure and a nonsubsampled directional filter to achieve multidimensional and translation-invariant image decomposition for spatial images. A nonsubsampled contourlet transform is used as the basis for an improved Bayesian nonlocal means (NLM) filter for different frequencies. The Bayesian model adds a sigma range in image a priori operations, which can be more effective in protecting image details. The NLM filter retains the image edge content and assigns greater weight to similarities for edge pixels. Experimental results both on standard images and spatial images confirm that the proposed algorithm yields significantly better performance than nonsubsampled wavelet transform, contourlet, and curvelet approaches. |
| format | Article |
| id | doaj-art-8d6a36db4efd4ffd935e083cb74540a3 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-8d6a36db4efd4ffd935e083cb74540a32025-02-03T00:59:20ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/467412467412Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet TransformPengcheng Han0Junping Du1Beijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaBeijing Key Laboratory of Intelligent Telecommunication Software and Multimedia, School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSpatial images are inevitably mixed with different levels of noise and distortion. The contourlet transform can provide multidimensional sparse representations of images in a discrete domain. Because of its filter structure, the contourlet transform is not translation-invariant. In this paper, we use a nonsubsampled pyramid structure and a nonsubsampled directional filter to achieve multidimensional and translation-invariant image decomposition for spatial images. A nonsubsampled contourlet transform is used as the basis for an improved Bayesian nonlocal means (NLM) filter for different frequencies. The Bayesian model adds a sigma range in image a priori operations, which can be more effective in protecting image details. The NLM filter retains the image edge content and assigns greater weight to similarities for edge pixels. Experimental results both on standard images and spatial images confirm that the proposed algorithm yields significantly better performance than nonsubsampled wavelet transform, contourlet, and curvelet approaches.http://dx.doi.org/10.1155/2012/467412 |
| spellingShingle | Pengcheng Han Junping Du Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform Journal of Applied Mathematics |
| title | Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform |
| title_full | Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform |
| title_fullStr | Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform |
| title_full_unstemmed | Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform |
| title_short | Spatial Images Feature Extraction Based on Bayesian Nonlocal Means Filter and Improved Contourlet Transform |
| title_sort | spatial images feature extraction based on bayesian nonlocal means filter and improved contourlet transform |
| url | http://dx.doi.org/10.1155/2012/467412 |
| work_keys_str_mv | AT pengchenghan spatialimagesfeatureextractionbasedonbayesiannonlocalmeansfilterandimprovedcontourlettransform AT junpingdu spatialimagesfeatureextractionbasedonbayesiannonlocalmeansfilterandimprovedcontourlettransform |