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An effective quality improvement scheme of magnified image using the surface characteristics in image

영상의 곡면 특성을 활용한 효과적인 확대영상의 화질 향상 기법

  • Jung, Soo-Mok (Division of Computer, Sahmuook University) ;
  • On, Byung-Won (Dept. of Statistics & Computer Science, Kunsan National University)
  • 정수목 (삼육대학교 컴퓨터학부) ;
  • 온병원 (군산대학교 통계컴퓨터과학과)
  • Received : 2014.07.28
  • Accepted : 2014.08.19
  • Published : 2014.08.30

Abstract

In this paper, we proposed an effective quality improvement scheme of magnified image using the surface characteristics in image. If the surface in image is estimated as simple convex surface or simple concave surface, the interpolated value can be calculated to have the surface characteristics by using the other method in the proposed scheme. The calculated value becomes the interpolated pixel value inmagnified image. So, themagnified image reflects the surface characteristics of the real image. If the surface is not estimated as simple convex surface or simple concave surface, the interpolated value is calculated more accurately than bilinear interpolation by using the method of the proposed scheme. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

본 논문에서는 확대영상의 화질을 향상시키기 위하여 영상의 곡면 특성을 활용한 효과적인 영상 확대 기법을 제안하였다. 제안된 기법에서 제시된 방법으로 영상의 단순 볼록 곡면 혹은 단순 오목 곡면을 효과적으로 추정하고, 단순 볼록 곡면 혹은 단순 오목 곡면으로 추정된 경우에는 확대하고자 하는 원본영상으로 역방향 사상된 좌표에서의 보간 값을 제안된 기법에서 제시된 효율적인 방법으로 계산하여 해당곡면의 특성을 잘 반영하는 보간 값을 구한 후 이를 확대영상의 보간 픽셀 값으로 하여 확대영상이 실제영상의 곡면 특성을 충실히 반영하도록 하였다. 또한 단순 볼록 곡면 혹은 단순 오목 곡면이 아닐 경우에는 역방향 사상된 좌표 주위의 기준 픽셀들의 영향을 더욱 정교하게 반영하도록 보간 값을 구하고 이를 확대영상의 보간 픽셀 값으로 한다. 실제 영상에 존재하는 단순 볼록 곡면 혹은 단순 오목 곡면의 특성을 더욱 충실히 반영하여 실제영상에 더욱 근접한 확대영상을 구성하도록 하기 위하여 위의 절차를 반복적으로 적용하여 확대영상을 구성하였다. 제안된 기법을 적용한 확대영상들의 PSNR(Peak Signal to Noise Ratio) 값이 기존의 기법들을 적용한 확대영상들보다 큰 것을 실험을 통해 확인하였다.

Keywords

References

  1. J. Shi, and S. E. Reichenbach, "Image Interpolation by Two-Dimensional Parametric Cubic Convolution," IEEE Trans. on Image Processing, Vol. 15, No. 7, pp. 1857-1870, July 2006. https://doi.org/10.1109/TIP.2006.873429
  2. S. M. Guo, C. Y. Hsu, G. C. Shin, and C. W. Chen, " Fast Pixel-size-based Large-scale Enlargement and Reduction of Image: Adaptive Combination of Bilinear Interpolation and Discrete Cosine Ttransform," Journal of Electronic Imaging, Vol. 20, No. 3, 2011.
  3. Y. C. Hu, W. L. Chen, and J. R. Zeng, "Adaptive Image Zooming based on Bilinear Interpolation and VQ Approximation," Communications in Computer and Information Science, Vol. 260, pp. 310-319, 2011. https://doi.org/10.1007/978-3-642-27183-0_33
  4. K. B. Kim, "Panoramic Image Improvement using Forward Warping and Bilinear Interpolation Method," Journal of the Korea Institute of Information and Communication Engineering," Vol. 16. No. 10, pp. 2108-2112, Oct., 2012. https://doi.org/10.6109/jkiice.2012.16.10.2108
  5. H. M. Moon, and S. B. Pan, "The LDA-based Long Distance Face Recognition using Multiple Distance Face Image and Bilinear Interpolation," Journal of Korean Institute of Information Technology," Vol. 11, No. 3, pp. 95-101, Mar., 2013.
  6. A. K. Jain, "Fundamentals of Digital Image Processing," Prentice Hall, 2005.
  7. Y. Bai, and H. Zhuang, "On the Comparison of Bilinear, Cubic Spline, and Fuzzy Interpolation Techniques for Robotic Position Measurements," IEEE Transactions on Instrumentation and Measurement, Vol. 54, Issue 6, pp. 2281-2288, Dec., 2005. https://doi.org/10.1109/TIM.2005.858563
  8. K. P. Hong, J. K. Wang, I. S. Reed, and W. S. Hsieh, "Image Data Compression using Cubic Convolution Spline Interpolation," IEEE Tran. Image Processing, Vol. 9, No. 11, pp. 1988-1995, Nov., 2000. https://doi.org/10.1109/83.877222
  9. X. Li, M. Orchard, "New edge-directed interpolation," IEEE Trans. Image Process, Vol. 10, No. 10, pp. 1521-1527, Oct., 2001. https://doi.org/10.1109/83.951537
  10. J. W. Hwang, and H. S. Lee, "Adaptive image interpolation based on local gradient features," IEEE Signal Processing Letters, Vol. 11, No. 3, pp.359-362, 2004. https://doi.org/10.1109/LSP.2003.821718
  11. T. W. Chan, O. C. Au, T. S. Chong, and W. S. Chau, "An Adaptive interpolation using spatial varing filter," IEEE Int. Conf. Consumer Electron, pp. 109-110, 2005.
  12. T. Mori, K. Kameyama, Y. Ohmiya, and J. Lee, "Image Resolution Conversion Based on an Edge-Adaptive Interpolation Kernel," IEEE Pacific Rim Conference, pp. 497-500, 2007.
  13. S. M. Jung, "An efficient quality improvement scheme for magnified image by using simple convex surface and simple concave surface characteristics in image," Journal of The Korea Society of Computer and Information, Vol. 18, No. 11, pp. 59-68, 2013.

Cited by

  1. 영상의 다양한 곡면 특성을 효과적으로 활용한 확대 영상의 화질 개선 기법 vol.20, pp.1, 2015, https://doi.org/10.9708/jksci.2015.20.1.063