Quantum image edge detection using improved Sobel mask based on NEQR

Recently, image edge detection using quantum image processing has focused due to having less circuit complexity and storage capacity. Edge extraction using the Sobel operator has the restriction in vertical and horizontal directions, which provides less edge information. In this paper, we introduce a quantum improved Sobel edge detection algorithm with non-maximum suppression and double threshold techniques for novel enhanced quantum representation method. We have analyzed the quantum circuit of realizing the edge detection algorithm, the number of edge pixels, simulation results, and circuit complexity. Thereafter, we have compared with the classical and some existing quantum edge detection algorithms. Our proposed algorithm can achieve a significant improvement in the case of edge information and circuit complexity.

Automated summary

This study introduces a quantum improved Sobel edge detection algorithm with non-maximum suppression and double threshold techniques, providing more edge information. By analyzing the quantum circuit, number of edge pixels, simulation results, and circuit complexity, it is found that this algorithm achieves significant improvements in edge information and circuit complexity. The algorithm is compared with classical and existing quantum edge detection algorithms, showing superior performance.