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컬러 이미지 변환을 이용한 노이즈 제거 방법 및 성능 비교

Performance comparison of Image De-nosing Techniques based on Color Model Transformation

  • 김태호 (청나 달튼 스쿨) ;
  • 김학란 (미시시피 주립대학교 계산공학과)
  • Kim, Taeho (Cheongna Dalton School) ;
  • Kim, Hakran (Department of Computational Engineering, Mississippi State University)
  • 투고 : 2017.10.31
  • 심사 : 2017.12.25
  • 발행 : 2017.12.31

초록

본 논문의 주요 목적은 컬러 이미지에서의 노이즈 제거를 위한 다양한 필터들의 성능 분석 비교이다. 기존의 노이즈 제거 필터들에 대한 분석에서 한 발 더 나아가 RGB에서 HSV나 $YC_BC_R$로 컬러 모델변환을 하여 노이즈를 제거하는 방법을 제안하였다. 논문에서 사용된 예인 Median, Wiener, Mean 등의 노이즈 제거필터들의 성능 개선에 도움을 주기위해 고안했으며 현재까지는 컬러 이미지를 위한 필터들의 성능분석이나 컬러모델 변환을 이용한 개선 방법들이 제안된 바가 없다. 이에 영감을 받아서, 고안된 새로운 방법을 테스트 하였다. 실행해 본 결과, 현재 사용되고 있는 필터들 중에서 몇몇 필터들의 성능을 향상시켜서 컬러 이미지에서의 노이즈 제거에 큰 도움을 주는 것으로 나타났다.

The main purpose of this paper is to compare the performances of various filters with color images to remove the noise. Furthermore, we suggest a modified de-noising process by the transformation of color model from RGB to another color models, such as HSV and $YC_BC_R$, to improve the quality of de-noising methods encompassing Median, Wiener, and Mean filters. Neither the performance comparison of the de-noising filters with color images nor the converting the color model for better de-noise on the degraded images haven't been performed before. Inspired to make improvements, we conduct experiments with new de-noising process on color images. The result of the experiments is shown that it could assist on certain filters being more reliable techniques.

키워드

참고문헌

  1. S Park, D Kim, H Im, H Kim, J Paek, J Park, Y Seo, "AEMSER Using Adaptive Threshold Of Canny Operator To Extract Scene Text," Journal of Digital Contents Society, Vol 16, No 6, December 2015, pp.951-959. https://doi.org/10.9728/dcs.2015.16.6.951
  2. Jaegyung Paek, Yeong Geon Seo, "Extracting the Slope and Compensating the Image Using Edges and Image Segmentation in Real World Image," Journal of Digital Contents Society, Vol.17 No.5, Dec 2016, pp. 441-448. https://doi.org/10.9728/dcs.2016.17.5.441
  3. Kwang-man Ko, "Pattern Formalization Technique for Dynamic Analysis of the Medical Image Data," Journal of Digital Contents Society, Vol.17 No.3, June 2016, pp. 197-202. https://doi.org/10.9728/dcs.2016.17.3.197
  4. Hakran Kim, Velinda R. Calvert, Seongjai Kim, "Preservation of Fine Structures in PDE-Based Image Denoising," Advances in Numerical Analysis Vol 2012, Article ID 750146, 2012, 19 pages.
  5. Hakran Kim, Youngjoon Cha, Seongjai Kim, "Curvature Interpolation Method for Image Zooming," IEEE Trans. Image Processing Vol. 20 No. 7, 2011, pp. 1895-1903. https://doi.org/10.1109/TIP.2011.2107523
  6. Suresh Kuma, Papendra Kuma, Manoj Gupta, Ashok Kumar Nagawat, "Performance Comparison of Median and Wiener Filter in Image De-noising, " Internationational Journal of Computer Application(0973-8887)," Vol 12, No 4, pp.27-31. November 2010.
  7. James C. Church, Yixin Chen, and Stephen V. Rice, "A Spatial Median Filter for noise removal in digital images," Southeastcon, 2008. IEEE, April 2008
  8. Azadeh NooriHoshyar, AdelAl-Jumaily, Afsaneh NooriHoshyar, "Comparing the Performance of Various Filters on Skin Cancer Images," Procedia Computer Science Vol. 42, pp. 32 - 37, 2014 https://doi.org/10.1016/j.procs.2014.11.030
  9. Akanksha Jain, Prateek Naha,r, "Performance Comparison of two Image Denoising Algorithm at Different Noises," Internationational Journal of Emerging Technology and Advanced Engineering (0973-8887)," Vol 3, Issue 12, pp. 359-361. December 2013.
  10. Saravanan C , Ponalagusamy R, "Gaussian Noise Estimation Technique for Gray Scale Images Using Mean Value," Journal of Theoretical and Applied Information Technology, (2005-2007), pp. 68-75.
  11. I. Pitas, A. Venetsanopoulos, "Nonlinear mean filters in image processing," IEEE Transactions on Acoustics, Speech, and Signal Processing , Volume: 34, Issue: 3, pp. 573 - 584, Jun 1986 https://doi.org/10.1109/TASSP.1986.1164857
  12. Ioannis Pitas, Anastasios N. Venetsanopoulos, "Nonlinear Digital Filters: Principles and Applications," Springer Science & Business Media, 2013
  13. Kenneth R. Castleman, Digital Image Processing. Prentice Hall, 1996.
  14. Eli Turkel, a professor of applied Mathematics at School of Mathematical Sciences, Tel Aviv University, Summary Wiener Filters[Internet] Available: http://www.math.tau.ac.il/-turkel/notes/wiener7-2.pdf
  15. R. C. Gonzales, R,E, Woods, Digital Image Processing, 2nd Edition, Prentice Hall, 2002
  16. Image processing learning resources, Mean filter[internet] Available: https://homepages.inf.ed.ac.uk/rbf/HIPR2/hipr_top.htm
  17. Keith Jack. Video demystified: a handbook for the digital engineer. Elsevier, 2011.
  18. David Salomon, "A Guide to Data Compression Methods," Springer Science & Business Media, 2013.