Abstract
Image super-resolution means forming high-resolution images from low-resolution images. In this paper, we develop a new approach based on the deep Restricted Boltzmann Machines (RBM) for image super-resolution. The RBM architecture has ability of learning a set of visual patterns, called dictionary elements from a set of training images. The learned dictionary will be then used to synthesize high resolution images. We test the proposed algorithm on both benchmark and natural images, comparing with several other techniques. The visual quality of the results has also been assessed by both human evaluation and quantitative measurement.
| Original language | English |
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| Title of host publication | 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings |
| Place of Publication | United States |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 449-453 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479923410 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 20th IEEE International Conference on Image Processing: ICIP 2013 - Melbourne Convention and Exhibition Centre, Melbourne, Australia Duration: 15 Sept 2013 → 18 Sept 2013 https://www2.securecms.com/ICIP2013/ |
Conference
| Conference | 2013 20th IEEE International Conference on Image Processing |
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| Country/Territory | Australia |
| City | Melbourne |
| Period | 15/09/13 → 18/09/13 |
| Other | The International Conference on Image Processing (ICIP), sponsored by the IEEE Signal Processing Society, is the premier forum for the presentation of technological advances and research results in the fields of theoretical, experimental, and applied image and video processing. ICIP 2013, the twentieth in the series that has been held annually since 1994, brings together leading engineers and scientists in image and video processing from around the world. |
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