A Novel Approach for Satellite Image Resolution Enhancement
E. Mohan1, K.B. Jayarraman2, U. Maheswaran3, D. Sathiyaraj4. G.Dhakshanamoorthi5
1E.Mohan, Head, Department of Computer Science and Engineering, Pallavan College of Engineering, Kanchipuram, India.
2Dr. K.B. Jayarraman, Head, Department of Computer Science and Engineering,, Manakula Vinayagar Institute of Technology, Pudhuchery, India.
3U. Maheswaran, Assistant Professor, Department of Electronics and Communication Engineering, Pallavan College of Engineering, Kanchipuram, India.
4D. Sathiyaraj, Assistant Professor, Department of Electronics and Communication Engineering, Pallavan College of Engineering, Kanchipuram, India.
5G. Dhakshana Moorthi, PG Scholar, Department of Computer Science and Engineering, Manakula Vinayagar Institute of Technology, Pudhuchery, India.
Manuscript received on March 22, 2013. | Revised Manuscript received on April 18, 2013. | Manuscript published on April 30, 2013. | PP: 112-114 | Volume-2, Issue-4, April 2013. | Retrieval Number: D1312042413/2013©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 resolution is an important issue in satellite imaging. Wavelets play a significant role in multi resolution analysis. In this paper, a new resolution enhancement technique is proposed. This method is based on interpolation of the high frequency sub-bands which are obtained by performing Discrete Wavelet Transform (DWT) on input image. DWT separates the image in to different sub-band images namely, low-low (LL), low-high (LH), high-low (HL) and high-high (HH). Interpolation can be applied to these four sub-band images. In the wavelet domain, the low-resolution image is obtained by low-pass filtering of the high-resolution image. The low-resolution image (LL sub-band) is used as input for the proposed resolution enhancement process. The high frequency sub-bands contain the high frequency components of image .Interpolation is carried out using Adjacent pixel algorithm and Inverse Discrete Wavelet Transform(IDWT) has been applied to combine all these images to generate the final super-resolved image. This approach generates sharper and clearer image. The proposed technique has shown superiority over the conventional image resolution enhancement techniques.
Keywords: Adjacent Pixel algorithm, DWT (discrete wavelet transform), Image Enhancement, Interpolation, Adjacent Pixel algorithm.