Paruvelli Sreedevi
ABSTRACT
We propose a novel single image super-resolution technique that combines an example-based approach and an unsharp mask image enhancement approach in a three-layer Markov network structure. The single image super-resolution problem is formulated as an optimization problem in the Markov network. We derive the maximum-a-posterior (MAP) solution of the problem by an iterative process in which the MAP is the fixed point solution. To evaluate our algorithm, we compare its results with those of state-of-the-art methods and a commercial product.
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Index Terms
- Example-based single image enhanced up-sampling
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