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Quantum image edge extraction based on classical robinson operator
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DOI：10.1007/s11042-022-12627-3.png)
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Abstract
En 中文
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 2(n) x 2(n) is O(n(2) + 2(q+ 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.
Keywords:
Quantum computing
Quantum image edge extraction
Robinson operator
Quantum circuits
Quantum image processing
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W