DOI码：10.1142/s0217732322501395
论文名称：A quantum segmentation algorithm based on local adaptive threshold for NEQR image
发表刊物：Modern Physics Letters A
关键字：Quantum image processing, quantum image segmentation, local adaptive threshold, quantum comparator, quantum subtractor
摘要：The classical image segmentation algorithm based on local adaptive threshold can effectively segment images with uneven illumination, but with the increase of the image data, the real-time problem gradually emerges. In this paper, a quantum segmentation algorithm based on local adaptive threshold for NEQR image is proposed, which can use quantum mechanism to simultaneously compute local thresholds for all pixels in a gray-scale image and quickly segment the image into a binary image. In addition, several quantum circuit units, including median calculation, quantum binarization, etc. are designed in detail, and then a complete quantum circuit is designed to segment NEQR images by using fewer qubits and quantum gates. For a 2n × 2n image with q gray-scale levels, the complexity of our algorithm can be reduced to O(n2 + q), which is an exponential speedup compared to the classic counterparts. Finally, the experiment is conducted on IBM Q to show the feasibility of our algorithm in the noisy intermediate-scale quantum (NISQ) era.
论文类型：期刊论文
论文编号：(2022) 2250139
文献类型：J
卷号：37
期号：22
页面范围：2250139
是否译文：否
发表时间：2022-09-06
收录刊物：SCI