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A Fuzzy Rule-Based Approach to Single Frame Super Resolution| old_uid | 15691 |
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| title | A Fuzzy Rule-Based Approach to Single Frame Super Resolution |
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| start_date | 2015/05/28 |
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| schedule | 11h15 |
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| online | no |
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| location_info | 25-26 |
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| summary | High quality image zooming is an important problem. The literature is rich with many methods for it. Some of the methods use multiple low resolution (LR) images of the same scene with different sub-pixel shifts as input to generate the high resolution (HR) images, while there are others, which use just one LR image to obtain the HR image. In this talk we shall discuss a novel fuzzy rule based single frame super resolution scheme. This is a patch based method, where for zooming each LR patch is replaced by a HR patch generated by a Takagi-Sugeno type fuzzy rule-based system. We shall discuss in details the generations of the training data, the initial generation of the fuzzy rules, refinement of the rules, and how to use such rules for generation of SR images. In this context we shall also discuss a Gaussian Mixture Regression (GMR) model for the same problem. To demonstrate the effectiveness and superiority of the proposed fuzzy rule-based system, we shall compare its performance with that of six methods including the GMR method in terms of multiple quality criteria. |
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| oncancel | séance annulée |
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| responsibles | Piwowarski |
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