Image magnification method based on linear interpolation and wavelet and PDE

  • Authors:

  • Changxiong Zhou;Chunmei Lu;Yubo Tian;Chuanlin Zhou

  • Affiliations:

  • Department of Electronic and Informational Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China;Department of Electronic and Informational Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China;School of Electronics and Information, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China;School of Physics and Electronic Information Engineering, Xiaogan College, Xiaogan, Hubei, China

  • Venue:
  • ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
  • Year:
  • 2011

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Abstract

This paper proposes a novel image magnification method based on bilinear interpolation, wavelet, and partial differential equation (PDE) techniques. The image which is interpolated linearly is decomposed by wavelet into a low frequency component image and three high frequency component images, and then the three high frequency component images and the original image regarded as low-frequency component will be used for image magnification by invert wavelet transform. Finally, a PDE involving gray fidelity constraint item called improvement-self-snake mode is presented in post-processing of the magnified image. The experimental results show that the proposed linear interpolation-wavelet-PDE approach is indeed efficient and effective in image magnification. In addition, we also compare the signal-to-noise ratio (SNR) of the linear interpolation-wavelet-PDE magnification method with methods of linear interpolation, linear interpolation-wavelet, and wavelet-PDE. The simulating results show that the linear interpolation-wavelet-PDE method indeed outperforms the three kinds of image magnification approaches mentioned above.