Image Super Resolution Reconstruction using Wavelet Transform Method
V. Prasath1, R.Buvanesvari2, N. Thilartham3, K. Nirosha4
1Mr. V.Prasath, Department of Computer Science & Engineering, Pondicherry University, PKIET Karaikal U.T (Puducherry), India.
2Mrs. R.Buvanesvari, Department of Computer Science & Engineering, Pondicherry University, PKIET Karaikal U.T (Puducherry), India.
3Ms. N.Thilartham, Department of Computer Science & Engineering, Pondicherry University, PKIET Karaikal U.T (Puducherry), India.
4Ms. K.Nirosha, Department of Computer Science & Engineering, Pondicherry University PKIET Karaikal U.T (Puducherry), India.
Manuscript received on 13 February 2014 | Revised Manuscript received on 20 February 2014 | Manuscript Published on 28 February 2014 | PP: 107-109 | Volume-3 Issue-9, February 2014 | Retrieval Number: I1496023914/14©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Image super-resolution (SR) has been extensively studied to solve the problem of limited resolution in imaging devices for decades. This paper addresses the problem of recovering a super-resolved image from a set of warped blurred and decimated versions thereof. Several algorithms have already been proposed for the solution of this general problem. In this paper, we propose the image super-resolution reconstruction using wavelet transform method. By using multi surface fitting the low resolution pixel image is converted to high resolution image. The super resolution image is then formed using interpolation based method. The noise and the blur in the resulting image are reduced using our wavelet transform method.
Keywords: Data Fusion, Multi Surface Fitting, Super Resolution, Stationary Wavelet Transform.
Scope of the Article: Data Mining Methods, Techniques, and Tools