Improved dual-threshold quantum image segmentation algorithm and simulation

Abstract Quantum image segmentation algorithm is crucial for quantum image processing. In this paper, a dual-threshold quantum image segmentation algorithm is designed and simulated in IBM Quantum Experience (IBM Q) platform, which can segment a complex image into three parts using fewer quantum bits. In our algorithm, given a high threshold and a low threshold, grayscale values larger than the high threshold are set to the high threshold and grayscale values smaller than the low threshold are set to the low threshold, with no change for the part between the two thresholds. Then we use a low-cost quantum comparator and design a complete and scalable quantum image segmentation circuit. Analysis of the circuit cost shows that the quantum gates required for the circuit are only related to the grayscale range q and are independent of the image size. The feasibility of the algorithm and the correctness of the quantum circuit are verified by simulation in IBM Q platform, and finally the MSE, PSNR AND SSIM value of the image is analyzed to prove the effectiveness of the segmentation algorithm.