Single Image Super-Resolution VIA Iterative Back Projection Based Canny Edge Detection and a Gabor Filter Prior
Rujul R Makwana1, Nita D Mehta2
1Rujul R Makwana, PG Student, Department of Electronics & Communication, Government Engineering College, Surat, India.
2Professor Nita D Mehta, Department of Electronics & Communication, Government Engineering College, Surat, India.
Manuscript received on February 04, 2013. | Revised Manuscript received on February 27, 2013. | Manuscript published on March 05, 2013. | PP: 379-384 | Volume-3 Issue-1, March 2013. | Retrieval Number: A1363033113/2013©BEIESP
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© The Authors. Published By: 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: The Iterative back-projection (IBP) is a classical super-resolution method with low computational complexity that can be applied in real time applications. This paper presents an effective novel single image super resolution approach to recover a high resolution image from a single low resolution input image. The approach is based on an Iterative back projection (IBP) method combined with the Canny Edge Detection and Gabor Filter to recover high frequency information. This method is applied on different natural gray images and compared with different existing image super resolution approaches. Simulation results show that the proposed algorithms can more accurately enlarge the low resolution image than previous approaches. Proposed algorithm increases the MSSIM and the PSNR and decreases MSE compared to other existing algorithms and also improves visual quality of enlarged images.
Keywords: Canny Edge Detection, Gabor Filter, IBP, Super Resolution.