Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Iterative grouping median filter for removal of fixed value impulse noise

© The Institution of Engineering and Technology
Received 18/10/2018, Accepted 02/01/2019, Revised 14/12/2018, Published 17/01/2019

Due to the limitation of existing filters in detection and removal of fixed value impulse noise, the authors propose an iterative grouping median filter (IGMF) according to the characteristics of noise intensity and distribution. It sorts the noise-free pixels in neighbourhood by intensity, divides the sorted pixels into groups depending on the intensity differences of adjacent pixels, and finally takes the median of the maximum group as the intensity of noisy pixel. This noise removal strategy is performed iteratively and takes full advantage of the previous denoising results. Experiments show that IGMF outperforms the existing state-of-the-art filters in terms of visual perception, peak signal to noise ratio and structural similarity index at various noise densities.

Inspec keywords: image denoising; median filters; filtering theory; impulse noise

Other keywords: existing state-of-the-art filters; noise-free pixels; adjacent pixels; fixed value impulse noise; noise intensity; intensity differences; noisy pixel; noise densities; iterative grouping median filter; maximum group; sorted pixels; noise removal strategy; noise ratio

Subjects: Computer vision and image processing techniques; Filtering methods in signal processing; Optical, image and video signal processing

References

    1. 1)
      • 24. Zhang, C.B., Wang, K.F.: ‘A switching median-mean filter for removal high-density impulse noise from digital images’, Optik, 2015, 126, (9–10), pp. 956–961.
    2. 2)
      • 5. Roy, A., Singha, J., Manam, L., et al: ‘Combination of adaptive vector median filter and weighted mean filter for removal of high-density impulse noise from colour images’, IET Image Process., 2017, 11, (6), pp. 352–361.
    3. 3)
      • 26. Li, Z., Liu, G., Xu, Y., et al: ‘Modified directional weighted filter for removal of salt & pepper noise’, Pattern Recognit. Lett., 2014, 40, (1), pp. 113–120.
    4. 4)
      • 6. Sadi, F., Lee, S.Y., Hasan, M.K.: ‘Removal of ring artifacts in computed tomographic imaging using iterative center weighted median filter’, Comput. Biol. Med., 2010, 40, (1), pp. 109–118.
    5. 5)
      • 17. Lu, C.T., Chou, T.C.: ‘Denoising of salt-and-pepper noise corrupted image using modified directional-weighted-median filter’, Pattern Recognit. Lett., 2012, 33, (10), pp. 1287–1295.
    6. 6)
      • 30. Esakkirajan, S., Veerakumar, T., Subramanyam, A.N., et al: ‘Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter’, IEEE Signal Process. Lett., 2011, 18, (5), pp. 287–290.
    7. 7)
      • 33. Balasubramanian, G., Chilambuchelvan, A., Vijayan, S., et al: ‘Probabilistic decision based filter to remove impulse noise using patch else trimmed median’, AEU-Int. J. Electron. Commun., 2016, 70, (4), pp. 471–481.
    8. 8)
      • 7. Lianghai, J., Dehua, L.: ‘Adaptive center-weighted median filter’, J. Huazhong Univ. Sci. Technol., 2008, 36, (8), pp. 9–12.
    9. 9)
      • 14. Jafar, I.F., Alna'Mneh, R.A., Darabkh, K.A.: ‘Efficient improvements on the BDND filtering algorithm for the removal of high-density impulse noise’, IEEE Trans. Image Process., 2013, 22, (3), pp. 1223–1232.
    10. 10)
      • 4. Villar, S.A., Torcida, S., Acosta, G.G.: ‘Median filtering: a new insight’, J. Math. Imaging Vis., 2016, 58, (1), pp. 1–17.
    11. 11)
      • 27. Hosseini, H., Hessar, F., Marvasti, F.: ‘Real-time impulse noise suppression from images using an efficient weighted-average filtering’, IEEE Signal Process. Lett., 2015, 22, (8), pp. 1050–1054.
    12. 12)
      • 32. Vijaykumar, V.R., Santhanamari, G.: ‘New decision-based trimmed median filter for high-density salt-and-pepper noise removal in images’, J. Electron. Imaging, 2014, 23, (3), pp. 1–14.
    13. 13)
      • 34. Wang, Z., Bovik, A.C., Sheikh, H.R., et al: ‘Image quality assessment: from error visibility to structural similarity’, IEEE Trans. Image Process., 2004, 13, (4), pp. 600–612.
    14. 14)
      • 21. Gao, G., Liu, Y.: ‘An efficient three-stage approach for removing salt & pepper noise from digital images’, Optik, 2015, 126, (4), pp. 467–471.
    15. 15)
      • 8. Meher, S.K.: ‘Recursive and noise-exclusive fuzzy switching median filter for impulse noise reduction’, Eng. Appl. Artif. Intell., 2014, 30, (2014), pp. 145–154.
    16. 16)
      • 23. Vijaykumara, V.R., Santhana Maria, G., Ebenezerb, D.: ‘Fast switching based median-mean filter for high density salt and pepper noise removal’, AEU-Int. J. Electron. Commun., 2014, 68, (12), pp. 1145–1155.
    17. 17)
      • 19. Khan, S., Lee, D.H.: ‘An adaptive dynamically weighted median filter for impulse noise removal’, EURASIP J. Adv. Signal Process., 2017, 2017, (67), pp. 1–4.
    18. 18)
      • 12. Ng, P.E., Ma, K.K.: ‘A switching median filter with boundary discriminative noise detection for extremely corrupted images’, IEEE Trans. Image Process., 2006, 15, (6), pp. 1506–1516.
    19. 19)
      • 18. Faragallahac, O.S., Ibrahemb, H.M.: ‘Adaptive switching weighted median filter framework for suppressing salt-and-pepper noise’, AEU-Int. J. Electron. Commun., 2016, 70, (8), pp. 1034–1040.
    20. 20)
      • 22. Hussain, A., Habib, M.: ‘A new cluster based adaptive fuzzy switching median filter for impulse noise removal’, Multimedia Tools Appl., 2017, 76, (21), pp. 22001–22018.
    21. 21)
      • 31. Feng, J.B., Ding, M.Y., Zhang, X.M.: ‘Decision-based adaptive morphological filter for fixed-value impulse noise removal’, Optik, 2014, 125, (16), pp. 4288–4294.
    22. 22)
      • 20. Cao, Y., Li, Y.Q.: ‘Switching median and morphological filter for impulse noise removal from digital images’, Optik, 2015, 126, (18), pp. 1598–1601.
    23. 23)
      • 29. Wang, Y., Han, L., Xiao, S., et al: ‘A novel statistical approach to remove salt-and-pepper noise’, J. Stat. Comput. Simul., 2017, 87, (13), pp. 2538–2548.
    24. 24)
      • 2. Jomaa, H., Mabrouk, R., Khlifa, N., et al: ‘Denoising of dynamic PET images using a multi-scale transform and non-local means filter’, Biomed. Signal Process. Control, 2018, 41, pp. 69–80.
    25. 25)
      • 13. Nasimudeen, A., Nair, M.S., Rao, T.: ‘Directional switching median filter using boundary discriminative noise detection by elimination’, Signal Image Video Process., 2012, 6, (4), pp. 613–624.
    26. 26)
      • 1. Lin, P.H., Chen, B.H., Cheng, F.C., et al: ‘A morphological mean filter for impulse noise removal’, J. Disp. Technol., 2016, 12, (4), pp. 344–350.
    27. 27)
      • 3. Rakshit, M., Das, S.: ‘An efficient ECG denoising methodology using empirical mode decomposition and adaptive switching mean filter’, Biomed. Signal Process. Control, 2018, 40, pp. 140–148.
    28. 28)
      • 9. Wangac, Y., Fub, J., Adhamia, R., et al: ‘A novel learning-based switching median filter for suppression of impulse noise in highly corrupted color images’, Imaging Sci. J., 2016, 64, (1), pp. 15–25.
    29. 29)
      • 25. Chen, Q.Q., Hung, M.H., Zou, F.: ‘Effective and adaptive algorithm for pepper-and-salt noise removal’, IET Image Process., 2017, 11, (9), pp. 709–716.
    30. 30)
      • 16. González-Hidalgo, M., Massanet, S., Mir, A., et al: ‘Improving salt and pepper noise removal using a fuzzy mathematical morphology-based filter’, Appl. Soft Comput., 2018, 63, pp. 167–180.
    31. 31)
      • 15. Balasubramanian, G., Chilambuchelvan, A., Vijayan, S., et al: ‘An extremely fast adaptive high-performance filter to remove salt and pepper noise using overlapping medians in images’, J. Photogr. Sci., 2016, 64, (5), pp. 241–252.
    32. 32)
      • 11. Çalışkan, A., Çevik, U.: ‘An efficient noisy pixels detection model for CT images using extreme learning machines’, Teh. vjesn., 2018, 25, (3), pp. 679–686.
    33. 33)
      • 28. Zhang, P., Li, F.: ‘A new adaptive weighted mean filter for removing salt-and-pepper noise’, IEEE Signal Process. Lett., 2014, 21, (10), pp. 1280–1283.
    34. 34)
      • 10. Mújica-Vargas, D., Funes, F.J.G., Rubio, J.D.J., et al: ‘Impulsive noise filtering using a Median Redescending M-Estimator’, Intell. Data Anal., 2017, 21, (3), pp. 739–754.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2018.6331
Loading

Related content

content/journals/10.1049/iet-ipr.2018.6331
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address