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A study on genetic expression programming-based approach for impulse noise reduction in images

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Abstract

Existing impulse noise reduction techniques perform well at low noise densities; however, their performance drops sharply at higher noise densities. In this paper, we propose a two-stage scheme to surmount this problem. In the proposed approach, first stage consists of impulse detection unit followed by the filtering operation in the second stage. We have employed a genetic expression programming-based classifier for the detection of impulse noise-corrupted pixels. To reduce the blurring effect caused due to filtering operation on the noise-free pixels, we filter the detected noisy pixels only by using a modified median filter. Better peak signal-to-noise ratio, structural similarity index measure, and visual output imply the efficacy of the proposed scheme for noise reduction at higher noise densities.

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Notes

  1. ‘Etilism’ is the cloning of best chromosomes to next population or generation.

  2. For the simplicity of expressing the mathematical equations, we have used arbitrary variables for 2, 3, and 4 variable operators by \((x,y), (x,y,z)\), and \((a,b,c,d)\), respectively. We have considered a post-order traversing scheme to represent the actual variables (represented by leaves in the ET) by the arbitrary variables mentioned above.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology, Agartala, 799055, Tripura (West), India

    Vivek Singh Bhadouria & Dibyendu Ghoshal

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  1. Vivek Singh Bhadouria
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  2. Dibyendu Ghoshal
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Correspondence to Vivek Singh Bhadouria.

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Bhadouria, V.S., Ghoshal, D. A study on genetic expression programming-based approach for impulse noise reduction in images. SIViP 10, 575–584 (2016). https://doi.org/10.1007/s11760-015-0780-6

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  • DOI: https://doi.org/10.1007/s11760-015-0780-6

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