Dynamic Approaches for Enhancing Single Image Super-Resolution Using Gradient Profile Sharpness Technique

Authors

  • V. Shanmugappriya Student, Chettinad college of Engineering and Technology, Karur, Tamil Nadu India

DOI:

https://doi.org/10.51983/ajcst-2016.5.1.1765

Keywords:

Single-image super-resolution, Gradient profile sharpness, Gaussian mixture model, Segmentation

Abstract

In this paper, we propose an image super-resolution approach using a gradient profile prior, which is a parametric prior describing the shape and the sharpness of the image gradients. Generate high resolution image from a low resolution input image single image super resolution is used. Single image super resolution is used to enhance the quality of image. In this paper there is a image super resolution algorithm is proposed which is based on GPS Gradient Profile Sharpness. Indicate the superior performance of the proposed algorithm compared to the leading super-resolution algorithms in the literature over a set of natural images in sharp edges and corners.

References

A. Buades, B. Coll, and J. M. Morel, "A non local algorithm for image denoising," in IEEE Conference on Computer Vision and Pattern Recognition, 2005.

H. Chang, D.-Y. Yeung, and Y. Xiong, "Super-resolution through neighbor embedding," in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, 2004, pp. 275–282.

S. Dai, M. Han, W. Xu, Y. Wu, and Y. Gong, "Soft edge smoothness prior for alpha channel super resolution," in IEEE Conference on Computer Vision and Pattern Recognition, 2007.

M. Ebrahimi and E. Vrscay, "Solving the inverse problem of image zooming using self-examples," in International Conference on Image Analysis and Recognition, 2007, pp. 117–130.

R. Fattal, "Upsampling via imposed edge statistics," ACM Transactions on Graphics, vol. 26, no. 3, 2007.

G. Freedman and R. Fattal, "Image and video upscaling from local self-examples," ACM Transactions on Graphics, vol. 28, no. 3, pp. 1–10, 2011.

W. T. Freeman, T. R. Jones, and E. C. Pasztor, "Example-based super-resolution," IEEE Computer Graphics and Applications, vol. 22, pp. 56–65, 2002.

Y. Freund, S. Dasgupta, M. Kabra, and N. Verma, "Learning the structure of manifolds using random projections," in NIPS, 2007.

D. Glasner, S. Bagon, and M. Irani, "Super-resolution from a single image," in IEEE International Conference on Computer Vision, 2009.

H. He and W. C. Siu, "Single image super-resolution using gaussian process regression," in CVPR, 2011.

D. Martin, C. Fowlkes, D. Tal, and J. Malik, "A , G. Yu, G. Sapiro and S. Mallat, 'Image modeling and enhancement via structured sparse model selection,'" in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2010, pp. 1641-1644.

J. Yang, J. Wright, T.S. Huang and Y. Ma, "Image super-resolution via sparse representation," IEEE Trans. Image Process., vol. 19, no. 11, 2010, pp. 2861-2873.

R. Zeyde, M. Elad and M.Protter, "On single image scale-up using sparse representations," Curves and Surfaces, Avignon-France, vol. 6920, 2010, pp. 711-730.

J. Kumar, F.Chen and D. Doermann, "Sharpness estimation for document and scene images," in Proc. 21st International Conference on Pattern Recognition (ICPR), 2012, pp. 3292-3295.

L. He, H. Qi and R. Zaretzki, "Beta process joint dictionary learning for coupled feature spaces with application to single image super-resolution," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2013, pp. 345-352.

R.C. Gonzalez and R.E. Woods, Digital image processing, 2nd edn. Prentice-Hall, Inc, Englewood Cliffs, NJ, 2002.

J. Sun, Z. Xu and H.Y.Shum, "Image super-resolution using gradient profile prior," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), 2008, pp. 1-8.

[Online]. Available: http://see.xidian.edu.cn/faculty/wsdong/wsdong_downloads.htm

M. Aharon, M. Elad and A.M. Bruckstein, "The K-SVD: an algorithm for designing of overcomplete dictionaries for sparse representations," IEEE Trans. Signal Process., vol. 54, no. 11, 2006, pp. 4311-4322.

Z. Wang, A.C. Bovik, H.R. Sheikh and E.P. Simoncelli, "Image quality assessment: from error visibility to structural similarity," IEEE Trans. Image Process., vol. 13, no. 4, 2004, pp. 600-612.

Downloads

Published

28-01-2016

How to Cite

Shanmugappriya, V. (2016). Dynamic Approaches for Enhancing Single Image Super-Resolution Using Gradient Profile Sharpness Technique. Asian Journal of Computer Science and Technology, 5(1), 6–9. https://doi.org/10.51983/ajcst-2016.5.1.1765