An adaptive algorithm for BAS optimization with variable step size and its application in image registration

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Nov.2024, Vol.47 No.11: 1465-1471

DOI: 10.3969/j.issn.1003-5060.2024.11.005

Authors

ZHANG Jinfeng $ ^{1} $, XIE Feng $ ^{2} $, WANG Peng $ ^{1} $, WU Rui $ ^{2} $, YU bo $ ^{3} $, DU Haibo $ ^{3} $

(1. State Grid Anhui Electric Power Co., Ltd., Hefei 230061, China; 2. China Energy Engineering Group Anhui Electric Power Design Institute Co., Ltd., Hefei 230601, China; 3. School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

Abstract and Keywords

Abstract: In response to the problems of high image distortion and blurred images due to the lack of spectral information in the existing remote sensing technology, this paper proposes a strategy to improve the resolution of remote sensing image based on oblique photography technology. The traditional beetle antennae search algorithm (BAS) has the advantages of fewer parameters, fast convergence speed, and easy implementation when dealing with image matching, but the accuracy is limited. In this paper, in the basic resolution of the step size, the variable step size search is carried out by making the step size decay exponentially. At the same time, referring to the particle swarm optimization strategy, the best position of the left and right whisker of BAS is introduced as the reference position of the next solution search to improve the solution search speed. Compared with the traditional BAS, the improved BAS proposed in this paper has higher solving accuracy. Finally, the effectiveness of the method is verified by experiments.

Keywords: remote sensing image; oblique photography; improved beetle antennae search algorithm (BAS); image registration and fusion

作者信息

张金锋 $ ^{1} $，谢枫 $ ^{2} $，王鹏 $ ^{1} $，吴睿 $ ^{2} $，俞波 $ ^{3} $，都海波 $ ^{3} $

（1. 国网安徽省电力有限公司，安徽合肥 230061；2. 中国能源建设集团安徽省电力设计院有限公司，安徽合肥 230601；3. 合肥工业大学电气与自动化工程学院，安徽合肥 230009）

摘要和关键词

摘要: 针对现有遥感技术缺乏光谱信息而导致图像失真度高、成像模糊等问题, 文章提出基于倾斜摄影技术提高遥感图像分辨率的方法。传统的天牛须算法(beetle antennae search algorithm, BAS) 在处理图像匹配时, 虽然具有参数少、收敛速度快、易于实现等优点, 但是精度有限。因此以步长指数衰减的方式进行变步长搜索, 同时借鉴粒子群算法寻优策略, 引入天牛左右须历史最佳位置作为下一步解的搜索参考位置, 以此提高解的搜索速度。与传统的天牛须智能优化算法相比, 该文提出的基于自适应变异的变步长天牛须算法求解精度更高, 通过实验验证了该算法的有效性。

关键词: 遥感图像；倾斜摄影图像；改进的天牛须算法(BAS)；图像配准与融合

Funding

安徽省能源互联网联合基金重点资助项目（2008085UD03）

合肥工业大学学报(自然科学版)

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