基于小波粗糙集算法的图像拼接研究

李宏升; 张健

doi:10.3788/YJYXS20142902.0298

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基于小波粗糙集算法的图像拼接研究

成像技术与图像处理 | 更新时间：2020-08-12

- 基于小波粗糙集算法的图像拼接研究
- Image mosaic research based on wavelet and rough set algorithm
- 液晶与显示 2014年29卷第2期页码：298-303
- 作者机构：
  
  黄淮学院信息工程学院,河南驻马店,463000
- 作者简介：
- 基金信息：
  
  河南省科技厅项目（No.122102310557）()
- DOI：10.3788/YJYXS20142902.0298
  中图分类号： TP393
- 收稿日期：2013-12-06，
  
  修回日期：2013-12-08，
  
  纸质出版日期：2014-03-05
- 稿件说明：
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李宏升, 张健. 基于小波粗糙集算法的图像拼接研究[J]. 液晶与显示, 2014,29(2): 298-303

LI Hong-sheng, ZHANG Jian. Image mosaic research based on wavelet and rough set algorithm[J]. , 2014,29(2): 298-303
李宏升, 张健. 基于小波粗糙集算法的图像拼接研究[J]. 液晶与显示, 2014,29(2): 298-303 DOI： 10.3788/YJYXS20142902.0298.

LI Hong-sheng, ZHANG Jian. Image mosaic research based on wavelet and rough set algorithm[J]. , 2014,29(2): 298-303 DOI： 10.3788/YJYXS20142902.0298.

摘要

为了提高图像拼接的质量，采用小波粗糙集算法。首先，基于自适应小波变换对图像分解，通过小波方向的对比度设定阈值来平衡图像内各个对象的差异。接着，分解图像特征点的粗糙决策属性来划分重叠区域，通过空间的划分，把上近似在属性子集的划分区域划分到对象集合中，下近似有可能划分到其他对象集合中，比较计算参考图像与输入图像特征向量因数集的欧氏距离约简规则选择特征点，并把输入图像中欧氏距离最小的点作为参考图像中特征点的匹配点。然后，通过平均值法消除拼接缝隙，实现图像的上下、左右以及斜方向的无缝拼接。最后，给出了算法流程和评价指标。实验仿真表明，本文算法拼接缝隙区域过渡光滑，视觉效果连续，没有出现重叠鬼影，本文算法的信息熵为33.872 1 bit，处理时间为2.436 8 s。满足拼接结果中对执行时间少、信息含量大等要求。

Abstract

In order to improve the quality of image mosaic

a wavelet and rough set algorithm is established.First

image is decomposed by adaptive wavelet transform

directions of the wavelet of image are set threshold to contrast and balance differences in individual object.Second

feature point is divi-ded the overlapped area

approximation properties in a subset of the divided region are divided into collection of object

lower approximation could be divided into other objects in the collection

reference and input feature vector factors of image are compared and ruled to Simple Euclidean Distance.Third

gap of image mosaic is eliminated by average method and disappeared in other directions.Finally

the whole process is described.The experiments show that this algorithm can made gap smoothly

visual appealing

without overlapping

and entropy of information is 33.872 1 bit

time are 2.436 8 s.It takes less time and has large information.

关键词

Keywords

references

陈德印. 360度全场景多目标识别与跟踪算法的研究与实现[D]. 南京:南京邮电大学, 2013. Chen D Y. Research and implementation of 360 degree full scene multiple target recognition and tracking algorithm[D].Nanjing:Nanjing University of Posts and Telecommunications, 2013.(in Chinese)[2] 王志刚, 夏汉铸. 一种基于鱼眼图像的全景展开算法[J]. 通信技术, 2012, 45(7):65-66, 71. Wang Z G, Xia H Z.A panoramic unwrapping algorithm based on fish-eye image[J].Communications Technology, 2012, 45(7):65-66, 71.(in Chinese)[3] 周强. 多重集相关投影分析与特征融合研究[D]. 南京:南京理工大学, 2011. Zhou Q. Study on the integration of multiple sets of correlation projection analysis and feature[D].Nanjing:Nanjing University of Posts and Telecommunications, 2011. (in Chinese)[4] 高保平, 白瑞林. 轴承压印字符自动识别算法的研究[J]. 电视技术, 2012, 36(9):142-145. GAO B P, BAI R L. Study on automatic recognition algorithm of pressed characters on bearing[J].Video Engineering, 2012, 36(9):142-145. (in Chinese)[5] 余胜, 谢莉, 成运. 基于颜色和基元特征的图像检索[J]. 计算机应用, 2013, 33(6):1674-1676. Yu S, Xie L, Cheng Y.Image retrieval based on color and motif characteristics[J].Journal of Computer Applications, 2013, 33(6):1674-1676. (in Chinese)[6] 马超杰, 李连喜. 基于SURF特征相关的红外图像自动拼接[J]. 淮海工学院学报, 2013, 22(1):19-21. Ma C J, Li L X. Infrared image automatic mosaic method based on SURF feather correlation[J].Journal of Huaihai Institute of Technology, 2013, 22(1):19-21. (in Chinese)[7] 纪东升. 基于特征点的图像拼接算法研究[D]. 兰州:兰州理工大学, 2011. Ji D S. Research on image mosaic algorithm based on feature points[D].Lanzhou: Lanzhou University of Technology, 2011. (in Chinese)[8] 王学伟, 王世立, 李珂. 基于伪中值滤波和小波变换的红外图像增强方法[J]. 激光与红外, 2013, 43(1):90-93. Wang X W, Wang S L, Li K. Infrared image enhancement based on pseudo median filter and wavelet transformation[J].Laser & Infrared, 2013, 43(1):90-93. (in Chinese)[9] 李钊宝, 周铭, 顾莉. 基于小波变换的相似多目标识别算法研究[J]. 科技通报, 2013, 29(3):120-124. Li Z B, Zhou M, Gu L.The identification algorithm of similarity multiple targets based on Wavelet transform[J].Bulletin of Science and Technology, 2013, 29(3):120-124. (in Chinese)[10] 丁南南, 刘艳滢, 朱明. 尺度相互作用墨西哥帽小波提取图像特征点[J]. 液晶与显示, 2012, 27(1): 125-129. Ding N N, Liu Y Y, Zhu M.Extracting image feature points using scale-interaction of Mexican-hat wavelets[J].Chinese Journal of Liquid Crystals and Displays, 2012, 27(1): 125-129. (in Chinese)[11] 姚军财. 基于人眼对比度敏感视觉特性的彩色图像压缩技术[J]. 液晶与显示, 2012, 27(6): 800-807. Yao J C.Color image compression technology based on contrast sensitivity characteristics of human vision system[J].Chinese Journal of Liquid Crystals and Displays, 2012, 27(6): 800-807. (in Chinese)[12] 蒲恬, 方庆吉, 倪国强. 基于对比度的多分辨率图像融合[J]. 电子学报, 2000, 28(12):116-118. Pu T, Fang Q J, Ni G Q.Multi resolution image fusion based on contrast[J].Acta Electronica Sinica, 2000, 28(12):116-118.(in Chinese)[13] 胡燕, 王慧琴, 秦薇薇, 等. 基于粗糙集的火灾图像特征选择与识别[J]. 计算机应用, 2013, 33(3):704-707. Hu Y, Wang H Q, Qin W W, et al.Fire image features selection and recognition based on rough set[J].Journal of Computer Applications, 2013, 33(3):704-707. (in Chinese)[14] 邵迎超, 杜召彬, 杨霁琳, 等. 软模糊粗糙集[J]. 计算机工程与应用, 2013, 49(10):125-128. Shao Y Y, Du Z B, Yang Q L, et al.Soft fuzzy rough sets[J].Computer Engineering and Applications, 2013, 49(10):125-128. (in Chinese)[15] 王学恩, 韩崇昭, 韩德强, 等. 粗糙集研究综述[J]. 控制工程, 2013, 20(1):1-8. Wang X E, Han C Z, Han D Q, et al.A survey of rough sets theory[J].Control Engineering of China, 2013, 20(1):1-8. (in Chinese)[16] 李淑尚, 李雷达, 何霁野, 等. 结合特征点与极谐变换的图像拼接[J]. 计算机工程与应用, 2013, 49(3):234-237. Li S S, Li L D, He J Y, et al.Image mosaic combining feature point and polar harmonic transform[J].Computer Engineering and Applications, 2013, 49(3):234-237. (in Chinese)[17] 卢鹏, 王锡淮, 肖健梅. 基于粗糙集和图论的电力系统故障诊断方法[J]. 控制与决策, 2013, 48(4):511-516, 524. Lu P, Wang X Z, Xiao J M. Method of fault diagnosis in power system based on rough set theory and graph theory[J].Control and Decision, 2013, 48(4):511-516, 524. (in Chinese)[18] 李军, 吴洁明. 一种改进图像拼接算法的仿真研究[J]. 计算机仿真, 2012, 29(2):273-276. Li J, Wu J M.Simulation research on improved image mosaic algorithm[J].Computer Stimulation, 2012, 29(2):273-276. (in Chinese)[19] 林小平, 周石琳, 张官亮, 等. 一种基于蚁群算法和互信息测度的图像拼接技术[J]. 重庆理工大学学报, 2013, 27(1):76-81. Lin X P, Zhou S L, Zhang G L, et al.An image mosaic technology based on ant colony algorithm and mutual information measure[J].Journal of Chongqing Institute of Technology, 2013, 27(1):76-81.(in Chinese)[20] 臧媛媛, 王正勇, 卿粼波. PTZ视频监控的大场景形成方法研究[J]. 四川大学学报, 2011, 48(3):577-583. Zang Y Y, Wang Z Y, Qing L B. The formation approach of wide-area scene in PTZ video surveillance[J].Journal of Sichuan University, 2011, 48(3):577-583.(in Chinese)

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