A quantum synthetic aperture radar image denoising algorithm based on grayscale morphology

被引：2

作者：

Wang, Lu ^{[1
,2
,3
]}

Liu, Yuxiang ^{[1
,3
,4
]}

Meng, Fanxu ^{[5
]}

Luan, Tian ^{[6
]}

Liu, Wenjie ^{[7
]}

Zhang, Zaichen ^{[1
,3
,4
,8
]}

Yu, Xutao ^{[1
,2
,3
,8
]}

机构：

[1] Southeast Univ, Sch Informat Sci & Engn, 2 Southeast Univ Rd, Nanjing 211189, Jiangsu, Peoples R China

[2] Southeast Univ, State Key Lab Millimeter Waves, 2 Southeast Univ Rd, Nanjing 211189, Jiangsu, Peoples R China

[3] Southeast Univ, Quantum Informat Ctr, 2 Southeast Univ Rd, Nanjing 211189, Jiangsu, Peoples R China

[4] Southeast Univ, Natl Mobile Commun Res Lab, 2 Southeast Univ Rd, Nanjing 211189, Jiangsu, Peoples R China

[5] Nanjing Tech Univ, Coll Artificial Intelligence, 30 Puzhu Nan Rd, Nanjing 211800, Jiangsu, Peoples R China

[6] Yangtze Delta Reg Ind Innovat Ctr Quantum & Inform, 286 Qinglong Gang Rd, Suzhou 215100, Jiangsu, Peoples R China

[7] Nanjing Univ Informat Sci & Technol, Sch Software, 219 Ning Liu Rd, Nanjing 210044, Jiangsu, Peoples R China

[8] Purple Mt Labs, 9 Mozhou Dong Rd, Nanjing 211111, Jiangsu, Peoples R China

来源：

ISCIENCE | 2024年 / 27卷 / 05期

基金：

中国国家自然科学基金;

关键词：

REPRESENTATION; SEGMENTATION; COMPRESSION; REALIZATION;

D O I：

10.1016/j.isci.2024.109627

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The quantum denoising technology efficiently removes noise from images; however, the existing algorithms are only effective for additive noise and cannot remove multiplicative noise, such as speckle noise in synthetic aperture radar (SAR) images. In this paper, based on the grayscale morphology method, a quantum SAR image denoising algorithm is proposed, which performs morphological operations on all pixels simultaneously to remove the noise in the SAR image. In addition, we design a feasible quantum adder to perform cyclic shift operations. Then, quantum circuits for dilation and erosion are designed, and the complete quantum circuit is then constructed. For a 2 n 3 2 n quantum SAR image with q grayscale levels, the complexity of our algorithm is O & eth; n + q & THORN; . Compared with classical algorithms, it achieves exponential improvement and also has polynomial -level improvements than existing quantum algorithms. Finally, the feasibility of our algorithm is validated on IBM Q.

引用

页数：9

共 43 条

[1]

Abd-El-Atty B, 2018, STUD BIG DATA, V33, P3, DOI 10.1007/978-3-319-63639-9_1

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