The synchronization of the images based on normalized mean square error algorithm

被引:10
|
作者
Pȩksiński J. [1 ]
Mikołajczak G. [1 ]
机构
[1] Faculty of Electrical Engineering, West Pomeranian University of Technology, Szczecin 71-126
来源
Advances in Intelligent and Soft Computing | 2010年 / 80卷
关键词
Compendex;
D O I
10.1007/978-3-642-14989-4_2
中图分类号
学科分类号
摘要
As it is known, to transform an analogue image into digital form it is necessary to undergo the processes of sampling and quantification. The first of them consists of downloading at defined intervals data from analogue image the second one approximates analogue levels of brightness due to the closest digital levels. Both processes are the reason of an errors formation. Those errors have significant influence on the fields of the digital images transformation, in which it is necessary to synchronize images. This problem becomes particularly significant when we use the images gained from two different sources (scanner, digital camera). Anyone who uses the terms concern to images' transformation, knows that bad synchronization can lead to wrong results. In his article authors present the algorithm which eliminates problem of bad images adjustment. The paper features the method of determination of the rotation angle and axis based on computation of the Normalized Mean Square Error (NMSE) coefficient. © 2010 Springer-Verlag Berlin Heidelberg.
引用
收藏
页码:15 / 25
页数:10
相关论文
共 40 条
  • [1] Fusion of correntropy and mean square error for sparse representaion based classification
    Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China
    不详
    Int Conf Signal Process Proc, (1234-1238):
  • [2] Direction of Arrival Estimation of Wideband Sources: Trend Analysis of Mean Square Error vs Regularization Parameters
    Sharma, Devki
    Santosh, Sandeep
    IEEE International Conference on Electrical, Electronics, Communication and Computers, ELEXCOM 2023, 2023,
  • [3] Noise suppression algorithm for chaotic mapping based on nonlocal mean
    Wang, Meng-Jiao
    Feng, Jiu-Chao
    Wu, Zhong-Tang
    Fang, Jie
    Wang, Qian
    Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science), 2015, 43 (05): : 40 - 44
  • [4] KNN-based mean shift algorithm for image segmentation
    Li, Yanling
    Shen, Yi
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2009, 37 (10): : 68 - 71
  • [5] A semi-blind synchronization algorithm based on the Filtered MultiTone system
    Liao, Jia-Chun
    Yao, Dong-Ping
    Ai, Bo
    Liu, Hong-Peng
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2013, 35 (06): : 1351 - 1356
  • [6] Anomaly target detection algorithm based on JPEG images
    Liu, Gaoping
    Zheng, Zihan
    2011 International Conference on Multimedia Technology, ICMT 2011, 2011, : 2952 - 2955
  • [7] Two-directional minimum squared error algorithm and classification experiments on face and building images
    Huang, Wei
    Wang, Xiaohui
    Jiang, Yuzhen
    Zhu, Yinghui
    Journal of Computational and Theoretical Nanoscience, 2015, 12 (11) : 4654 - 4660
  • [8] Swimming Attitude for Tracking Error Correction Based on Mahony Algorithm
    Chang, Zheng
    Zhao, Yu
    Mobile Information Systems, 2022, 2022
  • [9] Improved mean-shift based IR target tracking algorithm
    Hou, Qing-Yu
    Zhang, Wei
    Wu, Chun-Feng
    Lu, Li-Hong
    Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2010, 18 (03): : 764 - 770
  • [10] An improved particle swarm optimization algorithm for chaotic synchronization based on PID control
    Zou, Dexuan
    Wang, Xin
    Duan, Na
    Journal of Information and Computational Science, 2014, 11 (09): : 3177 - 3186