DOI码：10.1007/s11128-022-03624-4
论文名称：An improved two-threshold quantum segmentation algorithm for NEQR image
发表刊物：Quantum Information Processing
关键字：Quantum image processing Image segmentation Two-threshold Quantum comparator representation compression
摘要：The quantum image segmentation algorithm is to divide a quantum image into several parts, but most of the existing algorithms use more quantum resource(qubit) or cannot process the complex image. In this paper, an improved two-threshold quantum segmentation algorithm for NEQR image is proposed, which can segment the complex gray-scale image into a clear ternary image by using fewer qubits and can be scaled to use n thresholds for n + 1 segmentations. In addition, a feasible quantum comparator is designed to distinguish the gray-scale values with two thresholds, and then a scalable quantum circuit is designed to segment the NEQR image. For a 2(n)x2(n) image with q gray-scale levels, the quantum cost of our algorithm can be reduced to 60q-6, which is lower than other existing quantum algorithms and does not increase with the image's size increases. The experiment on IBM Q demonstrates that our algorithm can effectively segment the image.
论文类型：期刊论文
论文编号：(2022) 21:302
卷号：21
期号：8
是否译文：否
发表时间：2022-08-20
收录刊物：SCI