Abstract
As the resolution of output device increases, the demand of high resolution contents has become more eagerly. Therefore, the image super-resolution algorithms become more important. In digital image, the edges in the image are related to human perception heavily. Because of this, most recent research topics tend to enhance the image edges to achieve better visual quality. In this paper, we propose an edge-preserving image super-resolution algorithm by vectorizing the image edges. We first parameterize the image edges to fit the edges’ shapes, and then use these data as the constraint for image super-resolution. However, the color nearby the image edges is usually a combination of two different regions. The matting technique is utilized to solve this problem. Finally, we do the image super-resolution based on the edge shape, position, and nearby color information to compute a digital image with sharp edges.
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Hung, CJ., Huang, CK., Chen, BY. (2011). Image Super-Resolution by Vectorizing Edges. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_41
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DOI: https://doi.org/10.1007/978-3-642-17832-0_41
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