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An adaptive content based closer proximity pixel replacement algorithm for high density salt and pepper noise removal in images

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Abstract

An Adaptive Content based Closer Proximity Pixel Replacement algorithm for the removal of high density salt and pepper noise in images is proposed. The algorithm uses decision tree to identify and correct the pixels of the image is noisy or not. The algorithm finds Euclidean distance between the processed pixel and the number of non-noisy pixels inside the current processing kernel. The algorithm requires only two non-noisy pixels to be present in kernel for the algorithm to operate. The faulty pixels are replaced only by the median of pixels that occurs more frequently in the current processing kernel based on the Euclidean distance. The algorithm increases the window size by two when there are no non-noisy pixels in the current processing kernel. The proposed algorithm was compared with 16 standard and existing algorithms derived from recent literatures. Exhaustive experiments on standard database images suggest that the algorithm exhibit excellent noise suppression and good information preservation characteristics even at very high noise densities.

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Abbreviations

SPN:

Salt and pepper noise

ADKIF:

Adaptive decision based kriging interpolation filter

PSNR:

Peak signal to noise ratio

MSE:

Mean square error

IEF:

Image enhancement factor

ER:

Error rate

SSIM:

Structural Similarity Index metric

FOM:

Figure of merit

SMF:

Standard median filter

AMF:

Adaptive median filter

CWF:

Center weighted filter

αTMF:

Alpha trimmed mean filter

PSMF:

Progressive switched median filter

MDBMF:

Modified decision based median filter

DBA:

Decision based median algorithm

IDBA:

Improved decision based median filter

CUTMF:

Cascaded unsymmetrical trimmed mean filter

CUDBMPF:

Cascaded unsymmetrical decision based midpoint filter

MDBUTMF:

Modified decision based unsymmetrical trimmed median filter

MDBUTMF_GM:

Modified decision based unsymmetrical trimmed median filter with global mean

ACBSA:

Adaptive Cardinal B Spline interpolation filter

NAFSM:

Noise adaptive fuzzy switched median

AWMF:

Adaptive weighted mean filter

CPBD:

Cumulative probability blur detection metric

NCC:

Normalized correlation coefficient

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This Research did not receive any specific grant from funding agencies in the public, commercial or not for profit sectors.

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  1. K. Vasanth

    Present address: Department of E.C.E, Vidya Jyothi Institute of Technology, Aziz Nagar, Chilukur Road, Hyderabad, 500075, India

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, School of Electronics Engineering, Bharath University, Chennai, India

    R. Varatharajan

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Vasanth, K., Varatharajan, R. An adaptive content based closer proximity pixel replacement algorithm for high density salt and pepper noise removal in images. J Ambient Intell Human Comput (2020). https://doi.org/10.1007/s12652-020-02376-2

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