Abstract
This paper presents a novel significance driven inverse distance weighted (SDIDW) filter for the impulsive noise removal in the X-ray images. The proposed SDIDW filter restores the noisy pixel using minimum number of nearest noise-free pixels to achieve good estimation while exhibiting low computational complexity. In the proposed filter, higher priority (weight) is given to nearest pixels compared to distant pixels and only sufficient nearest noise free pixels are determined to estimate the value of noisy pixel. A high level analysis of the computation complexity at varying noise density is done which shows that proposed SDIDW filter provides significant reduction in computation complexity over the adaptive median filters. Finally, the performance of the proposed filter is evaluated and compared over the state-of-the-art impulse noise removal techniques for varying noise density (wide range 10–90% and very high noise density range 91–99%). The experimental results on medical images demonstrate significant improvement in filtered images quality by the proposed filter over the state-of-the-art filters at each sample of noise density with small computational complexity.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Ahmed F, Das S (2013) Removal of high-density salt-and-pepper noise in images with an iterative adaptive fuzzy filter using alpha-trimmed mean. IEEE Trans Fuzzy Syst 22(5):1352–1358
Aiswarya K, Jayaraj V, Ebenezer D (2010) A new and efficient algorithm for the removal of high density salt and pepper noise in images and videos. In: 2010 second international conference on computer modeling and simulation, vol 4. IEEE, pp 409–413
Arora S, Hanmandlu M, Gupta G (2018) Filtering impulse noise in medical images using information sets. Pattern Recogn Lett 139:1–9
Astola J, Kuosmanen P (1997) Fundamentals of nonlinear digital filtering, vol 8. CRC Press, Boca Raton
Balasubramanian G, Chilambuchelvan A, Vijayan S, Gowrison G (2016) Probabilistic decision based filter to remove impulse noise using patch else trimmed median. AEU Int J Electron Commun 70(4):471–481
Bhadouria VS, Ghoshal D, Siddiqi AH (2014) A new approach for high density saturated impulse noise removal using decision-based coupled window median filter. Signal Image Video Process 8(1):71–84
Brahme A (2014) Comprehensive biomedical physics. Newnes, Oxford
Chen J, Li F (2019) Denoising convolutional neural network with mask for salt and pepper noise. IET Image Process 13(13):2604–2613
Ching-Ta L, Chen Y-Y, Wang L-L, Chang C-F (2016) Removal of salt-and-pepper noise in corrupted image using three-values-weighted approach with variable-size window. Pattern Recognit Lett 80:188–199
Computer Vision and Pattern Recognition Group (2020). http://www.eng.usf.edu/cvprg/. Accessed July 2019
Erkan U, Gökrem L (2018) A new method based on pixel density in salt and pepper noise removal. Turk J Electr Eng Comput Sci 26(1):162–171
Erkan U, Gökrem L, Enginoğlu S (2018) Different applied median filter in salt and pepper noise. Comput Electric Eng 70:789–798
Esakkirajan S, Veerakumar T, Subramanyam Adabala N, PremChand CH (2011) Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter. IEEE Signal Process Lett 18(5):287–290
Faragallah OS, Ibrahem HM (2016) Adaptive switching weighted median filter framework for suppressing salt-and-pepper noise. AEU Int J Electron Commun 70(8):1034–1040
Garg Bharat (2020a) An adaptive minimum-maximum value-based weighted median filter for removing high density salt and pepper noise in medical images. Int J Ad Hoc Ubiquitous Comput 35(2):84–95
Garg B (2020b) Restoration of highly salt-and-pepper-noise-corrupted images using novel adaptive trimmed median filter. Signal Image Video Process 14:1555–1563
Garg B, Arya KV (2020) Four stage median-average filter for healing high density salt and pepper noise corrupted images. Multimed Tools Appl 79(43):32305–32329
Hoang TDN, Ngoc HN, Prasath S et al (2020) Adaptive total variation l1 regularization for salt and pepper image denoising. Optik 208:163677
Hwang H, Haddad RA (1995) Adaptive median filters: new algorithms and results. IEEE Trans Image Process 4(4):499–502
Li Z, Liu G, Yong X, Cheng Y (2014) Modified directional weighted filter for removal of salt & pepper noise. Pattern Recognit Lett 40:113–120
Murugan K, Arunachalam VP, Karthik S (2019) Hybrid filtering approach for retrieval of MRI image. J Med Syst 43(1):9
Ng P-E, Ma K-K (2006) A switching median filter with boundary discriminative noise detection for extremely corrupted images. IEEE Trans Image Process 15(6):1506–1516
Pitas I, Venetsanopoulos AN (2013) Nonlinear digital filters: principles and applications, vol 84. Springer, Berlin
Ramachandran V, Kishorebabu V (2019) A tri-state filter for the removal of salt and pepper noise in mammogram images. J Med Syst 43(2):40
Satti P, Sharma N, Garg B (2020) Min-max average pooling based filter for impulse noise removal. IEEE Signal Process Lett 27:1475–1479
Singh SPJ, Sharma N, Garg B, Arya KV (2021) Noise density range sensitive mean-median filter for impulse noise removal. In: Innovations in computational intelligence and computer vision. Springer, pp 150–162
Srinivasan KS, Ebenezer D (2007) A new fast and efficient decision-based algorithm for removal of high-density impulse noises. IEEE Signal Process Lett 14(3):189–192
Veerakumar T, Esakkirajan S, Vennila Ila (2014) Recursive cubic spline interpolation filter approach for the removal of high density salt-and-pepper noise. Signal Image Video Process 8(1):159–168
Vijaykumar VR, Santhana Mari G, Ebenezer D (2014) Fast switching based median—mean filter for high density salt and pepper noise removal. AEU Int J Electron Commun 68(12):1145–1155
Wang Z, Bovik AC, Sheikh HR, Simoncelli EP et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612
Woods RE, Gonzalez RC (2002) Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River
Zhang S, Karim MA (2002) A new impulse detector for switching median filters. IEEE Signal Process Lett 9(11):360–363
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Garg, B., Rana, P.S. & Rathor, V.S. Significance driven inverse distance weighted filter to restore impulsive noise corrupted X-ray image. J Ambient Intell Human Comput 13, 2013–2024 (2022). https://doi.org/10.1007/s12652-021-02962-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-021-02962-y