The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution
The nonsubsampled Contourlet transform (NSCT) not only retains the characteristics of Contourlet transform, but also has the good characteristic of shift-invariance, which plays a significant role in denoising, fusion, and segmentation of texture-rich images. The NSCT not only retains the properties...
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8493589/ |
| _version_ | 1818644547868033024 |
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| author | Xianghai Wang Ruoxi Song Chuanming Song Jingzhe Tao |
| author_facet | Xianghai Wang Ruoxi Song Chuanming Song Jingzhe Tao |
| author_sort | Xianghai Wang |
| collection | DOAJ |
| description | The nonsubsampled Contourlet transform (NSCT) not only retains the characteristics of Contourlet transform, but also has the good characteristic of shift-invariance, which plays a significant role in denoising, fusion, and segmentation of texture-rich images. The NSCT not only retains the properties of Contourlet transform, but also has the important property of shift-invariance, which plays a significant role in image processing, such as denoising, fusion, and segmentation of texture-rich images. This paper proposes a Gaussian-Cauchy mixture distribution-based NSCT hidden Markov tree model (GC-NSCT-HMT). The specific form of Gaussian-Cauchy mixture distribution is determined by the kurtosis of the NSCT coefficients in each subband. First, we study the probability density distribution of the remote sensing image NSCT coefficients and then propose the Gaussian-Cauchy mixture distribution, which can adaptively adjust according to the statistical property of NSCT coefficients through a balance function. Experimental results show that the proposed mixture distribution can achieve a good imitative effect to the NSCT coefficients. Second, we study the marginal statistical property and the joint statistical property of the NSCT coefficients, the persistence and aggregation properties of them are also studied in depth. We find that the ‘father’ NSCT coefficient can transfers to its son coefficients through a tree structure. Third, we combine the above conclusions with the hidden Markov tree model (HMT) and the GC-NSCT-HMT model is proposed. Finally, we apply our model to remote sensing image denoising. The subjective and objective experimental results demonstrate the feasibility of the proposed method. |
| first_indexed | 2024-12-17T00:16:35Z |
| format | Article |
| id | doaj.art-5b28fd22511a48e0b4d098a2fe0245f6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T00:16:35Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5b28fd22511a48e0b4d098a2fe0245f62022-12-21T22:10:42ZengIEEEIEEE Access2169-35362018-01-016660076601910.1109/ACCESS.2018.28764478493589The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture DistributionXianghai Wang0https://orcid.org/0000-0002-7600-9939Ruoxi Song1Chuanming Song2Jingzhe Tao3College of Computer and Information Technology, Liaoning Normal University, Dalian, ChinaSchool of Urban and Environmental Sciences, Liaoning Normal University, Dalian, ChinaCollege of Computer and Information Technology, Liaoning Normal University, Dalian, ChinaSchool of Urban and Environmental Sciences, Liaoning Normal University, Dalian, ChinaThe nonsubsampled Contourlet transform (NSCT) not only retains the characteristics of Contourlet transform, but also has the good characteristic of shift-invariance, which plays a significant role in denoising, fusion, and segmentation of texture-rich images. The NSCT not only retains the properties of Contourlet transform, but also has the important property of shift-invariance, which plays a significant role in image processing, such as denoising, fusion, and segmentation of texture-rich images. This paper proposes a Gaussian-Cauchy mixture distribution-based NSCT hidden Markov tree model (GC-NSCT-HMT). The specific form of Gaussian-Cauchy mixture distribution is determined by the kurtosis of the NSCT coefficients in each subband. First, we study the probability density distribution of the remote sensing image NSCT coefficients and then propose the Gaussian-Cauchy mixture distribution, which can adaptively adjust according to the statistical property of NSCT coefficients through a balance function. Experimental results show that the proposed mixture distribution can achieve a good imitative effect to the NSCT coefficients. Second, we study the marginal statistical property and the joint statistical property of the NSCT coefficients, the persistence and aggregation properties of them are also studied in depth. We find that the ‘father’ NSCT coefficient can transfers to its son coefficients through a tree structure. Third, we combine the above conclusions with the hidden Markov tree model (HMT) and the GC-NSCT-HMT model is proposed. Finally, we apply our model to remote sensing image denoising. The subjective and objective experimental results demonstrate the feasibility of the proposed method.https://ieeexplore.ieee.org/document/8493589/Gaussian-Cauchy mixture distributionNSCTHMTGC-NSCT-HMTremote sensing image denoising |
| spellingShingle | Xianghai Wang Ruoxi Song Chuanming Song Jingzhe Tao The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution IEEE Access Gaussian-Cauchy mixture distribution NSCT HMT GC-NSCT-HMT remote sensing image denoising |
| title | The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution |
| title_full | The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution |
| title_fullStr | The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution |
| title_full_unstemmed | The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution |
| title_short | The NSCT-HMT Model of Remote Sensing Image Based on Gaussian-Cauchy Mixture Distribution |
| title_sort | nsct hmt model of remote sensing image based on gaussian cauchy mixture distribution |
| topic | Gaussian-Cauchy mixture distribution NSCT HMT GC-NSCT-HMT remote sensing image denoising |
| url | https://ieeexplore.ieee.org/document/8493589/ |
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