Parameter estimation-based single image super resolution

In this paper, we introduce a parameter estimation-based single image super resolution technique. The basic idea of the proposed method is to use the property of unknown high resolution image inferred by relations of its lower resolution images. The proposed algorithm is consists of 3 main phases: 1) in the first step, an error model between an input and its lower resolution images is constructed for inferring the property of unknown high resolution image; 2) In the second step, global enhancement using estimated signal complexity and its strength is performed. 3) Lastly, independent enhancement in artifact candidate regions is performed in estimated artifact candidate regions with artifact removal using property of morphological operation. The experimental results show the efficiency of the proposed algorithm compared to a state-of-the-art method. Besides, the proposed method is not only much faster than the compared method but also able to implement in hard ware such as digital TVs and smart phones. Therefore, we believe that the proposed method can be a useful tool for super resolution-related consumer electronics fields.