DOI Number:10.1142/s0217732322501395

Journal:Modern Physics Letters A

Key Words:Quantum image processing, quantum image segmentation, local adaptive threshold, quantum comparator, quantum subtractor

Abstract: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.

Indexed by:Journal paper

Document Code:(2022) 2250139

Document Type:J

Volume:37

Issue:22

Page Number:2250139

Translation or Not:no

Date of Publication:2022-09-06

Included Journals:SCI