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Discrete and Stationary Wavelet Decomposition by Enhancing the Image Resolution


Affiliations
1 Gudlavalleru Engineering College, Iceland
2 Gudlavalleru Engineering College, India
     

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This work proposed an image resolution enhancement technique which is based on the interpolation of the high frequency subbands obtained by DWT. The proposed technique uses DWT to decompose an image into different subbands, and then the high frequency subband images have been interpolated. The interpolated high frequency subband coefficients have been corrected by using the high frequency subbands achieved by SWT of the input image. An original image is interpolated with half of the interpolation factor used for interpolation the high frequency subbands. Afterwards all these images have been combined using IDWT to generate a super resolved imaged. The proposed technique has been tested on well-known benchmark images, where their PSNR, Mean Square Error and Entropy results show the superiority of proposed technique over the conventional and state-of-art image resolution enhancement techniques.


Keywords

Discrete Wavelet Transform, Image Super Resolution, Stationary Wavelet Transform.
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  • Discrete and Stationary Wavelet Decomposition by Enhancing the Image Resolution

Abstract Views: 231  |  PDF Views: 3

Authors

Battula R. V. S. Narayana
Gudlavalleru Engineering College, Iceland
K. Nirmala
Gudlavalleru Engineering College, India

Abstract


This work proposed an image resolution enhancement technique which is based on the interpolation of the high frequency subbands obtained by DWT. The proposed technique uses DWT to decompose an image into different subbands, and then the high frequency subband images have been interpolated. The interpolated high frequency subband coefficients have been corrected by using the high frequency subbands achieved by SWT of the input image. An original image is interpolated with half of the interpolation factor used for interpolation the high frequency subbands. Afterwards all these images have been combined using IDWT to generate a super resolved imaged. The proposed technique has been tested on well-known benchmark images, where their PSNR, Mean Square Error and Entropy results show the superiority of proposed technique over the conventional and state-of-art image resolution enhancement techniques.


Keywords


Discrete Wavelet Transform, Image Super Resolution, Stationary Wavelet Transform.