Quantum image edge extraction based on improved Prewitt operator

Edge detection is one of the most important techniques in the field of image processing, which has a great influence on the subsequent research of feature extraction, description and target recognition. By analyzing the traditional Prewitt edge detection algorithm, the algorithm has been found some shortcomings, such as coarse edge detection and false edge detection caused by artificial selection of threshold. In this paper, quantum image edge extraction for the novel enhanced quantum representation (NEQR) is proposed based on improved Prewitt operator, which combines the non-maximum suppression method and adaptive threshold value method. The quantum image model of NEQR utilizes the superposition state of qubit sequence to store all the pixels of an image, which can calculate the gradients of the image intensity of all the pixels simultaneously. In addition, the non-maximal suppression can refine the edge, and the adaptive threshold can reduce the misjudgment of edge points. By analyzing the quantum circuit of realizing image edge extraction and the simulation results, compared with all the classical edge extraction algorithms and some existing quantum edge extraction algorithms, our proposed scheme can achieve a significant efficiency.