The complex Householder transform

1997 ◽  
Vol 45 (9) ◽  
pp. 2374-2376 ◽  
Author(s):  
Kuo-Liang Chung ◽  
Wen-Ming Yan
Keyword(s):  
Householder Transform

On the Householder Transform in Cm

1995 ◽  
Vol 5 (2) ◽  
pp. 116-117 ◽  
Author(s):  
X.G. Xia ◽  
B.W. Suter
Keyword(s):  
Householder Transform

Slant Plane CSAR Processing Using Householder Transform

2008 ◽  
Vol 17 (10) ◽  
pp. 1900-1907 ◽  
Author(s):  
J. Burki ◽  
C.F. Barnes
Keyword(s):  
Householder Transform

scholarly journals Efficient Realization of Householder Transform Through Algorithm-Architecture Co-Design for Acceleration of QR Factorization

2018 ◽  
Vol 29 (8) ◽  
pp. 1707-1720 ◽  
Author(s):  
Farhad Merchant ◽  
Tarun Vatwani ◽  
Anupam Chattopadhyay ◽  
Soumyendu Raha ◽  
S. K. Nandy ◽  
...  
Keyword(s):  
Qr Factorization ◽  
Householder Transform ◽  
Efficient Realization

Householder Transform in Cm

1993 ◽  
Vol 3 (4) ◽  
pp. 226-227 ◽  
Author(s):  
V.Ch. Venkaiah ◽  
V.V. Krishna ◽  
A. Paulraj
Keyword(s):  
Householder Transform

Robust Watermarking Using n-Diagonalization Based on Householder Transform

2014 ◽  
Vol 18 (4) ◽  
pp. 549-557
Author(s):  
Jaesung Park ◽  
◽  
Kazuhito Sawase ◽  
Hajime Nobuhara
Keyword(s):  
Image Watermarking ◽  
Singular Values ◽  
Discrete Wavelet ◽  
Robust Watermarking ◽  
Orthogonal Matrices ◽  
Information Quantity ◽  
Control Information ◽  
Value Decomposition ◽  
Householder Transform ◽  
Better Than

Digital image watermarking based on singular value decomposition (SVD) is highly robust against misuse, but lacks the ability to distinguish whether watermarks are correct due to the importance of singular values being lower than two orthogonal matrices. To achieve highly accurate watermark extraction while maintaining high robustness, we propose robust watermarking based on discrete wavelet transform (DWT) and n-diagonalization formalized by Householder transformation. We propose that DWT be used to ensure visibility and that n-diagonalization be used to control information quantity related to watermark extraction accuracy. Experimental results confirm the robustness of our proposed method and that the extraction accuracy of the proposed method is approximately 2 times better than that of SVD.

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