High Resolution Image Estimation using Restoration Technique
|International Journal of Mobile Computing and Application|
|© 2014 by SSRG - IJMCA Journal|
|Volume 1 Issue 2|
|Year of Publication : 2014|
|Authors : M.Meenakshi Devi|
M.Meenakshi Devi, "High Resolution Image Estimation using Restoration Technique" SSRG International Journal of Mobile Computing and Application 1.2 (2014): 8-12.
M.Meenakshi Devi,(2014). High Resolution Image Estimation using Restoration Technique. SSRG International Journal of Mobile Computing and Application 1(2), 8-12.
The blur, aliasing, and additive white Gaussian noise are artifacts which corrupts the low-resolution images. The simultaneous estimation of volatile blurs and high resolution images by using unified blind method. The complexity in super-resolution is solved by minimizing a regularization of energy function. The regularization is carried by both image and blur domains. Variational integral method for image regularization with good edgepreserving capabilities and blur regularization is based on blur estimation. The Huber-Markov random field (HMRF) model, is used for image regularization which is a type of variational integral that produce the piecewise smooth nature of the HR image. The supported blur estimation process is carried by using bilateral filtering and sharp filtering. An edge-emphasizing smoothing operation, which improves the quality of blur estimation by enhancing strong soft edges toward step edges and weak structures can be filtered.
 S. Farsiu, M. Robinson, M. Elad, and P. Milanfar, “Fast and robust multiframe super resolution,” IEEE Trans. Image Process., vol. 13,no. 10, pp. 1327–1344, Oct. 2004.
 W. Freeman, T. Jones, and E. Pasztor, “Example-based super-resolution,”IEEE Comput. Graph. Appl., vol. 22, no. 2, pp. 56–65, Mar.–Apr. 2002.
 D. Glasner, S. Bagon, and M. Irani, “Super-resolution from a single image,” in Proc. IEEE 12th Int. Conf. Comput. Vis., Sep. 2009, pp. 349–356.
 R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman,“Removing camera shake from a single photograph,” ACM Trans.Graph., vol. 25, pp. 787–794, Jul. 2006.
 Q. Shan, J. Jia, and A. Agarwala, “High-quality motion deblurring from a single image,” ACM Trans. Graph. (SIGGRAPH), vol. 27, no. 3,pp. 73:1–73:10, Aug. 2008.
Super-resolution, Blind deconvolution, Bilinear Interpolation, Huber-Markov Random Field, Bilateral filtering and Sharp filtering.