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Intensity bound limit filter for high density impulse noise removal

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Abstract

Digital images captured by electronic products are highly susceptible to salt & pepper noise during image acquisition, enrolment, preparation, and transmission phases. Therefore, it is essential to utilize superior image restoration methods to mitigate these effects. Additionally, in the restoration process, the preservation of edge data is essential as overall image quality can be severely degraded if the edge restoration processes underperform. In this paper, a novel two-stage intensity bound limit filter is proposed in which the denoised image is obtained via first stage generation of Intensity bound limit images and second stage recombination of the generated bound images. An interesting point to note is that the bound images preserve vital image edge data by extracting the infimum and supremum pixel values for any locality in the image. These separated bound images are subsequently utilized in a recombination stage to obtain the filtered image. Using this method, significant improvements in the boundary estimation are achieved especially in higher noise densities. Qualitative and quantitative analyses have been performed for standard, medical, and the Kodak image dataset which contains multiple colored images. Results show that the proposed algorithm outperforms state-of-the-art filters in terms of image detail restoration and overall noise removal. With respect to peak signal to noise ratio, an average improvement of 0.76 dB for standard images, 0.9 dB for medical images, and 1.03 db for Kodak dataset has been observed. A high-level hardware architecture has also been provided for the same.

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Abbreviations

dB:

Decibel

SAP:

Salt and pepper

PPP:

Previously processed pixel

IBL:

Intensity bound limit

BIL:

Bound image limit

FSM:

Finite state machine

RnS:

Recombination and smoothing

PSNR:

Peak signal to noise ratio

SSIM:

Structural similarity index measure

MSE:

Mean square error

ASWMF:

Adaptive switching weighted median filter

BPDM:

Based on pixel density filter

DAMF:

Dynamic adaptive median filter

FSBMMF:

Fast switching based median-mean filter

MDBUTMF:

Modified decision based unsymmetric trimmed median filter

RSIF:

Recursive cubic spline interpolation filter

SMF:

Standard median filter

SWMF:

Switching weighted median filter

TVWA:

Three-values-weighted approach

References

  • Appiah O, Asante M, Hayfron-Acquah JB (2022) Improved approximated median filter algorithm for real-time computer vision applications. J King Saud Univ-Comput Inf Sci 34:782–792

    Google Scholar 

  • Balasubramanian G, Chilambuchelvan A, Vijayan S, Gowrison G (2016) An extremely fast adaptive high-performance filter to remove salt and pepper noise using overlapping medians in images. Imaging Sci J 64(5):241–252

    Article  Google Scholar 

  • Chen J, Li F (2019) Denoising convolutional neural network with mask for salt and pepper noise. IET Image Proc 13(13):2604–2613

    Article  Google Scholar 

  • Eng H-L, Ma K-K (2001) Noise adaptive soft-switching median filter. IEEE Trans Image Process 10(2):242–251

    Article  MATH  Google Scholar 

  • Erkan U, GöKREM L (2018) A new method based on pixel density in salt and pepper noise removal. Turk J Electric Eng Comput Sci 26(1):162–171

    Article  Google Scholar 

  • Erkan U, Enginoğlu S, Thanh DN (2019) Adaptive frequency median filter for the salt and pepper denoising problem. IET Image Proc 14(7):1291–1302

    Article  Google Scholar 

  • Esakkirajan S, Veerakumar T, Subramanyam AN, PremChand C (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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Kumar SV, Nagaraju C (2021) Support vector neural network based fuzzy hybrid filter for impulse noise identification and removal from gray-scale image. J King Saud Univ-Comput Inf Sci 33:820–835

    Google Scholar 

  • Lu C-T, 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 Recogn Lett 80:188–199

    Article  Google Scholar 

  • Nair MS, Revathy K, Tatavarti R (2008) An improved decision-based algorithm for impulse noise removal. In: 2008 Congress on Image and Signal Processing, vol. 1: pp 426–431

  • 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

    Article  Google Scholar 

  • Patel P, Majhi B, Jena B, Tripathy C (2012) Dynamic adaptive median filter (damf) for removal of high density impulse noise. Int J Image Graph Signal Process 4(11):53

    Article  Google Scholar 

  • Satti P, Sharma N, Garg B (2020) Min-max average pooling based filter for impulse noise removal. IEEE Signal Process Lett 27:1475–1479

    Article  Google Scholar 

  • Thanh DN, Prasath VS, Phung TK, Hung NQ (2020a) Impulse denoising based on noise accumulation and harmonic analysis techniques. Optik 241:166163

    Article  Google Scholar 

  • Thanh DNH, Hien NN, Prasath S (2020b) Adaptive total variation l1 regularization for salt and pepper image denoising. Optik 208:163677

    Article  Google Scholar 

  • Veerakumar T, Esakkirajan S, Vennila I (2014) Recursive cubic spline interpolation filter approach for the removal of high density salt-and-pepper noise. SIViP 8(1):159–168

    Article  Google Scholar 

  • Vijaykumar V, Vanathi P, Kanagasabapathy P, Ebenezer D (2008) High density impulse noise removal using robust estimation based filter. IAENG Int J Comput Sci 35(3):1–8

    Google Scholar 

  • Vijaykumar V, Mari GS, 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

    Article  Google Scholar 

  • Wang Z, Zhang D (1999) Progressive switching median filter for the removal of impulse noise from highly corrupted images. IEEE Trans Circ Syst II Analog Digit Signal Process 46(1):78–80

    Article  Google Scholar 

  • Zhang S, Karim MA (2002) A new impulse detector for switching median filters. IEEE Signal Process Lett 9(11):360–363

    Article  Google Scholar 

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Acknowledgements

This research was funded by University of Economics Ho Chi Minh City, Vietnam. Fund receiver: Dr. Dang Ngoc Hoang Thanh.

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    Authors and Affiliations

    1. Electronics and Communication Engineering Department, Thapar Institute of Engineering and Technology, Bhadson Road, Patiala, Punjab, 147001, India

      Piyush Satti, Vaibhav Shrotriya & Bharat Garg

    2. Department of Information Technology, College of Technology and Design, University of Economics Ho Chi Minh City (UEH), Ho Chi Minh City, 70000, Vietnam

      Dang N. H. Thanh

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    1. Piyush Satti
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    2. Vaibhav Shrotriya
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    3. Bharat Garg
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    4. Dang N. H. Thanh
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    Correspondence to Bharat Garg.

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    Satti, P., Shrotriya, V., Garg, B. et al. Intensity bound limit filter for high density impulse noise removal. J Ambient Intell Human Comput 14, 12453–12475 (2023). https://doi.org/10.1007/s12652-022-04328-4

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