Energy-Driven Image Interpolation Using Gaussian Process Regression
Image interpolation, as a method of obtaining a high-resolution image from the corresponding low-resolution image, is a classical problem in image processing. In this paper, we propose a novel energy-driven interpolation algorithm employing Gaussian process regression. In our algorithm, each interpo...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/435924 |
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| _version_ | 1832566936851972096 |
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| author | Lingling Zi Junping Du |
| author_facet | Lingling Zi Junping Du |
| author_sort | Lingling Zi |
| collection | DOAJ |
| description | Image interpolation, as a method of obtaining a high-resolution image from the corresponding low-resolution image, is a classical problem in image processing. In this paper, we propose a novel energy-driven interpolation algorithm employing Gaussian process regression. In our algorithm, each interpolated pixel is predicted by a combination of two information sources: first is a statistical model adopted to mine underlying information, and second is an energy computation technique used to acquire information on pixel properties. We further demonstrate that our algorithm can not only achieve image interpolation, but also reduce noise in the original image. Our experiments show that the proposed algorithm can achieve encouraging performance in terms of image visualization and quantitative measures. |
| format | Article |
| id | doaj-art-25c7a5e2a41944909f89a30481c4b163 |
| 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-25c7a5e2a41944909f89a30481c4b1632025-02-03T01:02:43ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/435924435924Energy-Driven Image Interpolation Using Gaussian Process RegressionLingling Zi0Junping 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, ChinaImage interpolation, as a method of obtaining a high-resolution image from the corresponding low-resolution image, is a classical problem in image processing. In this paper, we propose a novel energy-driven interpolation algorithm employing Gaussian process regression. In our algorithm, each interpolated pixel is predicted by a combination of two information sources: first is a statistical model adopted to mine underlying information, and second is an energy computation technique used to acquire information on pixel properties. We further demonstrate that our algorithm can not only achieve image interpolation, but also reduce noise in the original image. Our experiments show that the proposed algorithm can achieve encouraging performance in terms of image visualization and quantitative measures.http://dx.doi.org/10.1155/2012/435924 |
| spellingShingle | Lingling Zi Junping Du Energy-Driven Image Interpolation Using Gaussian Process Regression Journal of Applied Mathematics |
| title | Energy-Driven Image Interpolation Using Gaussian Process Regression |
| title_full | Energy-Driven Image Interpolation Using Gaussian Process Regression |
| title_fullStr | Energy-Driven Image Interpolation Using Gaussian Process Regression |
| title_full_unstemmed | Energy-Driven Image Interpolation Using Gaussian Process Regression |
| title_short | Energy-Driven Image Interpolation Using Gaussian Process Regression |
| title_sort | energy driven image interpolation using gaussian process regression |
| url | http://dx.doi.org/10.1155/2012/435924 |
| work_keys_str_mv | AT linglingzi energydrivenimageinterpolationusinggaussianprocessregression AT junpingdu energydrivenimageinterpolationusinggaussianprocessregression |