Single frame image recovery for super resolution with parameter estimation of pearson type VII density
Image recovery of super resolution aims to recover a single high resolution image from one or more low resolution frames. It is an ill-posed problem when the solution does not exist or it is unique. Thus, we introduce the prior based on Pearson type VII density integrated with a Markov Random Field...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://ddms.usim.edu.my:80/jspui/handle/123456789/15344 |
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| Summary: | Image recovery of super resolution aims to recover a single high resolution image from one or more low resolution frames. It is an ill-posed problem when the solution does not exist or it is unique. Thus, we introduce the prior based on Pearson type VII density integrated with a Markov Random Field (MRF) model. We devise two different versions, one that acts on the pixel level and another one that acts on the entire image. Here we present our parameter estimation and evaluate our approach using qualitative measurement in both compressive measurement and classical super resolution. Our estimation is theoretically simple and easy to implement. |
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