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Quantum image edge extraction based on classical robinson operator

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Abstract

In this paper, a quantum image edge extraction technique is developed with the help of the classical Robinson operator. A novel enhanced quantum representation (NEQR) technique is used to represent the quantum image. A quantum methodology is proposed to implement the Robinson masks of eight directions and perform convolution operations with the quantum shifted image sets. In this paper, a quantum parallel computation is used for evaluating gradients of the image intensity of all pixels, and a threshold-based quantum black box is designed to classify the points as edge points. The computational complexity of the proposed scheme for an image of size 2n × 2n is O(n2 + 2q+ 3). However, we also carry out the design and simulation analysis of our proposed algorithm and finally compare our results with some state-of-art image edge extraction algorithms in terms of PSNR (peak signal to noise ratio), MSE (mean square error) and execution time.

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Acknowledgment

No research funding has been received for this work.

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Authors and Affiliations

  1. Computer Science and Engineering, JIS University, Kolkata, India

    Sanjay Chakraborty

  2. Computer Science and Engineering, BML Munjal University, Kapriwas, India

    Soharab Hossain Shaikh

  3. A.K.Choudhury School of IT, University of Calcutta, Kolkata, India

    Amlan Chakrabarti & Ranjan Ghosh

Authors
  1. Sanjay Chakraborty
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  2. Soharab Hossain Shaikh
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  3. Amlan Chakrabarti
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  4. Ranjan Ghosh
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Correspondence to Sanjay Chakraborty.

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Chakraborty, S., Shaikh, S.H., Chakrabarti, A. et al. Quantum image edge extraction based on classical robinson operator. Multimed Tools Appl 81, 33459–33481 (2022). https://doi.org/10.1007/s11042-022-12627-3

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  • DOI: https://doi.org/10.1007/s11042-022-12627-3

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