摘要
针对量子图像拼接使用传统尺度不变特征变换(SIFT)算法易造成特征点数量不合理和误匹配率高的问题,提岀基于动态阈值和全局信息的SIFT量子图像拼接算法.针对特征点数量问题,利用特征点数量与量子点或量子环数量呈正比例关系这一特性,通过量子点或环的密度对SIFT算法的对比度阈值进行设置,以得到合适的特征点数量.针对误匹配率问题,通过构建全局信息描述子,并与SIFT局部描述子相结合,以降低误匹配率.实验结果表明:改进的算法有效地完成了量子环、量子线和量子点图像的拼接;将量子图像的特征点有效地控制在一个合理的范围内,并将误匹配率从17.34%〜33.02%降低至10.84%〜20%,使量子图像的拼接具有更好的可靠性.
When it is applied to quantum image stitching,the traditional scale-invariant feature transform(SIFT)algorithm will result in the problems such as unreasonable feature point distribution and high mismatch rate.So an improved SIFT quantum image stitching algorithm based on dynamic threshold and global information is proposed.In the aspect of unreasonable feature point number,as the number is Jproportional to the number of quantum dots or quantum rings,the contras11hreshold of SIFT algorithm is set by calculating the density of quantum dots or rings so as to get the appropriate feature point number.In the aspec t of reducing high false mismatch rate,a global information descrip tor is cons tructed and combined with the local SIFT descrip tor.The experimental results show that the improved algorithm can effectively comple te the st itching of quantum rings,quantum wire and quantum dot images,effectively control the feature points of quantum images within a reasonable range,and reduce the mismatch rate from 17.34%~33.02% to 10.84%~20%,which makes the quantum image stitching have better reliability.
作者
唐泽恬
丁召
曾瑞敏
钟岷哲
朱登玮
王昱皓
王阳
杨晨
TANG Zetian;DING Zhao;ZENG Ruimin;ZHONG Minzhe;ZHU Dengwei;WANG Yuhao;WANG Yang;YANG Chen(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China;Power Semiconductor Device Reliability Engineering Center of the Ministry of Education,Guizhou University,Guiyang 550025,China;Longmaster Information and Technology Co.,Guiyang 550022,China)
出处
《量子电子学报》
CAS
CSCD
北大核心
2020年第1期22-28,共7页
Chinese Journal of Quantum Electronics
基金
国家自然科学基金,61604046
贵州省科技计划项目,黔科合平台人才[2017]5788号、[2018]5781号
半导体功率器件可靠性教育部工程研究中心开放基金,黔科合平台人才20176103号。
关键词
图像处理
尺度不变特征变换
量子图像
全局信息
动态阈值
image processing
scale-invariant feature transform
quantum image
global information
dy・namic threshold