Image reconstruction from a complete set of geometric and complex moments

被引:28
作者
Honarvar, Barmak x [1 ]
Paramesran, Raveendran [1 ]
Lim, Chern-Loon [1 ]
机构
[1] Univ Malaya, Fac Engn, Dept Elect, Kuala Lumpur 50603, Malaysia
关键词
Image reconstruction; Geometric moments; Complex moments; Stirling transform; Gaussian blur; PATTERN-RECOGNITION; TCHEBICHEF MOMENTS; HAHN MOMENTS; INVARIANTS;
D O I
10.1016/j.sigpro.2013.11.037
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
An image can be reconstructed from the finite set of its orthogonal moments. Since geometric and complex moment kernels do not satisfy orthogonality criterion, direct image reconstruction using them is deemed to be difficult. In this paper, we propose a technique to reconstruct an image from either geometric moments (GMs) or complex moments (CMs). We utilize a relationship between GMs and Stirling numbers of the second kind. Then, by using the invertibility property of the Stirling transform, the original image can be reconstructed from its complete set of either geometric or complex moments. Further, based on previous works on blur effects on a moment domain and using the proposed reconstruction methods, a formulation is shown to obtain an estimated original image from the degraded image moments and the blur parameter. The reconstruction performance of the proposed methods on blur images is presented to validate the theoretical framework. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:224 / 232
页数:9
相关论文
共 27 条
[1]   IMAGE NORMALIZATION BY COMPLEX MOMENTS [J].
ABUMOSTAFA, YS ;
PSALTIS, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1985, 7 (01) :46-55
[2]   Quaternion Zernike moments and their invariants for color image analysis and object recognition [J].
Chen, B. J. ;
Shu, H. Z. ;
Zhang, H. ;
Chen, G. ;
Toumoulin, C. ;
Dillenseger, J. L. ;
Luo, L. M. .
SIGNAL PROCESSING, 2012, 92 (02) :308-318
[3]   A local Tchebichef moments-based robust image watermarking [J].
Deng, Cheng ;
Gao, Xinbo ;
Li, Xuelong ;
Tao, Dacheng .
SIGNAL PROCESSING, 2009, 89 (08) :1531-1539
[4]   Classification of degraded signals by the method of invariants [J].
Flusser, J ;
Suk, T .
SIGNAL PROCESSING, 1997, 60 (02) :243-249
[5]   Invariants to convolution in arbitrary dimensions [J].
Flusser, J ;
Boldys, J ;
Zitová, B .
JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2000, 13 (02) :101-113
[6]  
Flusser J., 2009, Moments and Moment Invariants in Pattern Recognition
[7]   Image reconstruction from a complete set of similarity invariants extracted from complex moments [J].
Ghorbel, F. ;
Derrode, S. ;
Mezhoud, R. ;
Bannour, T. ;
Dhahbi, S. .
PATTERN RECOGNITION LETTERS, 2006, 27 (12) :1361-1369
[8]  
Ghorbel F., 2005, P INT C MACH INT ACI
[9]   Image representation using accurate orthogonal Gegenbauer moments [J].
Hosny, Khalid M. .
PATTERN RECOGNITION LETTERS, 2011, 32 (06) :795-804
[10]   VISUAL-PATTERN RECOGNITION BY MOMENT INVARIANTS [J].
HU, M .
IRE TRANSACTIONS ON INFORMATION THEORY, 1962, 8 (02) :179-&