Quantum image edge extraction based on classical robinson operator

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 × 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.