Stable analysis of large-size signals and images by Racah’s discrete orthogonal moments

2022 ◽  
Vol 403 ◽  
pp. 113830
Author(s):  
Achraf Daoui ◽  
Hicham Karmouni ◽  
Mhamed Sayyouri ◽  
Hassan Qjidaa
2019 ◽  
Vol 38 (8) ◽  
pp. 3715-3742 ◽  
Author(s):  
Hicham Karmouni ◽  
Tarik Jahid ◽  
Mhamed Sayyouri ◽  
Abdeslam Hmimid ◽  
Hassan Qjidaa

2014 ◽  
Vol 24 (2) ◽  
pp. 417-428 ◽  
Author(s):  
Haiyong Wu ◽  
Senlin Yan

Abstract This paper presents a new set of bivariate discrete orthogonal moments which are based on bivariate Hahn polynomials with non-separable basis. The polynomials are scaled to ensure numerical stability. Their computational aspects are discussed in detail. The principle of parameter selection is established by analyzing several plots of polynomials with different kinds of parameters. Appropriate parameters of binary images and a grayscale image are obtained through experimental results. The performance of the proposed moments in describing images is investigated through several image reconstruction experiments, including noisy and noise-free conditions. Comparisons with existing discrete orthogonal moments are also presented. The experimental results show that the proposed moments outperform slightly separable Hahn moments for higher orders.


2017 ◽  
Vol 71 ◽  
pp. 264-277 ◽  
Author(s):  
Imad Batioua ◽  
Rachid Benouini ◽  
Khalid Zenkouar ◽  
Azeddine Zahi ◽  
El Fadili Hakim

2007 ◽  
Vol 40 (2) ◽  
pp. 659-669 ◽  
Author(s):  
Bulent Bayraktar ◽  
Tytus Bernas ◽  
J. Paul Robinson ◽  
Bartek Rajwa

2019 ◽  
Vol 148 ◽  
pp. 428-437 ◽  
Author(s):  
O. El ogri ◽  
A. Daoui ◽  
M. Yamni ◽  
H. Karmouni ◽  
M. Sayyouri ◽  
...  

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