Abstract
Fractal image coding can specially utilize spatial information and self-similarity structural information of an image to achieve image super-resolution. However, fractal image coding based on single scale brings the problems of block effect and loss of details. In this paper we propose a multi-scale fractal coding method for single image super-resolution. The proposed method integrates the fractal results of different scales and uses back-projection to further optimize the result. Experimental results show that the proposed method can remove the block effect, improve the loss of details and keep smooth of flat area and sharpness of edges in the reconstructed image. Compared with conventional fractal coding and cubic splines interpolation, our method is superior to both of them subjectively and objectively.
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Xie, W., Liu, J., Shao, L., Jing, F. (2014). Multi-scale Fractal Coding for Single Image Super-Resolution. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_46
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DOI: https://doi.org/10.1007/978-3-319-09333-8_46
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
Online ISBN: 978-3-319-09333-8
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