The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Waleed A Ahmed - One of the best experts on this subject based on the ideXlab platform.
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hermite gaussian like eigenvectors of the discrete fourier Transform Matrix based on the direct utilization of the orthogonal projection matrices on its eigenspaces
IEEE Transactions on Signal Processing, 2006Co-Authors: M T Hanna, Nabila Philip Attalla Seif, Waleed A AhmedAbstract:A new version is proposed for the Gram-Schmidt algorithm (GSA), the orthogonal procrustes algorithm (OPA) and the sequential orthogonal procrustes algorithm (SOPA) for generating Hermite-Gaussian-like orthonormal eigenvectors for the discrete Fourier Transform Matrix F. This version is based on the direct utilization of the orthogonal projection matrices on the eigenspaces of Matrix F rather than the singular value decomposition of those matrices for the purpose of generating initial orthonormal eigenvectors. The proposed version of the algorithms has the merit of achieving a significant reduction in the computation time
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hermite gaussian like eigenvectors of the discrete fourier Transform Matrix based on the singular value decomposition of its orthogonal projection matrices
IEEE Transactions on Circuits and Systems, 2004Co-Authors: M T Hanna, Nabila Philip Attalla Seif, Waleed A AhmedAbstract:A technique is proposed for generating initial orthonormal eigenvectors of the discrete Fourier Transform Matrix F by the singular-value decomposition of its orthogonal projection matrices on its eigenspaces and efficiently computable expressions for those matrices are derived. In order to generate Hermite-Gaussian-like orthonormal eigenvectors of F given the initial ones, a new method called the sequential orthogonal procrustes algorithm (SOPA) is presented based on the sequential generation of the columns of a unitary Matrix rather than the batch evaluation of that Matrix as in the OPA. It is proved that for any of the SOPA, the OPA, or the Gram-Schmidt algorithm (GSA) the output Hermite-Gaussian-like orthonormal eigenvectors are invariant under the change of the input initial orthonormal eigenvectors.
M T Hanna - One of the best experts on this subject based on the ideXlab platform.
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hermite gaussian like eigenvectors of the discrete fourier Transform Matrix based on the direct utilization of the orthogonal projection matrices on its eigenspaces
IEEE Transactions on Signal Processing, 2006Co-Authors: M T Hanna, Nabila Philip Attalla Seif, Waleed A AhmedAbstract:A new version is proposed for the Gram-Schmidt algorithm (GSA), the orthogonal procrustes algorithm (OPA) and the sequential orthogonal procrustes algorithm (SOPA) for generating Hermite-Gaussian-like orthonormal eigenvectors for the discrete Fourier Transform Matrix F. This version is based on the direct utilization of the orthogonal projection matrices on the eigenspaces of Matrix F rather than the singular value decomposition of those matrices for the purpose of generating initial orthonormal eigenvectors. The proposed version of the algorithms has the merit of achieving a significant reduction in the computation time
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hermite gaussian like eigenvectors of the discrete fourier Transform Matrix based on the singular value decomposition of its orthogonal projection matrices
IEEE Transactions on Circuits and Systems, 2004Co-Authors: M T Hanna, Nabila Philip Attalla Seif, Waleed A AhmedAbstract:A technique is proposed for generating initial orthonormal eigenvectors of the discrete Fourier Transform Matrix F by the singular-value decomposition of its orthogonal projection matrices on its eigenspaces and efficiently computable expressions for those matrices are derived. In order to generate Hermite-Gaussian-like orthonormal eigenvectors of F given the initial ones, a new method called the sequential orthogonal procrustes algorithm (SOPA) is presented based on the sequential generation of the columns of a unitary Matrix rather than the batch evaluation of that Matrix as in the OPA. It is proved that for any of the SOPA, the OPA, or the Gram-Schmidt algorithm (GSA) the output Hermite-Gaussian-like orthonormal eigenvectors are invariant under the change of the input initial orthonormal eigenvectors.
Susanto Rahardja - One of the best experts on this subject based on the ideXlab platform.
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a robust watermarking scheme using sequency ordered complex hadamard Transform
Signal Processing Systems, 2011Co-Authors: Aye Aung, Susanto RahardjaAbstract:This paper presents a robust phase watermarking scheme for still digital images based on the sequency-ordered complex Hadamard Transform (SCHT). The Transform Matrix of the SCHT exhibits sequency ordering which is analogous to frequency in the discrete Fourier Transform (DFT). Hence, sequency-based image analysis can be performed for image watermarking while providing simple implementation and with less computational complexity for computation of the Transform. As the SCHT coefficients are complex numbers which consist of both magnitudes and phases, they are suited to adopt phase modulation techniques to embed the watermark. In this proposed scheme, the phases of the SCHT coefficients in the sequency domain are altered to convey the watermark information using the phase shift keying (PSK) modulation. Low amplitude block selection (LABS) is used to enhance the imperceptibility of digital watermark, and amplitude boost (AB) method is employed to improve the robustness of the watermarking scheme. Spread spectrum (SS) technique is adopted to increase the security of watermark against various unintentional or intentional attacks. In order to demonstrate the effectiveness of the proposed watermarking scheme, simulations are conducted under various kinds of attacking operations. The results show that the proposed scheme is able to sustain a series of attacks including common geometric Transformations such as scaling, rotating, cropping, painting, and common image-processing operations such as JPEG compression, low-pass filtering, sharpening, noising and phase perturbation, etc. Comparisons of the simulation results with the other schemes are also mentioned and the results reveal that the proposed scheme shows better robustness.
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conjugate symmetric sequency ordered complex hadamard Transform
IEEE Transactions on Signal Processing, 2009Co-Authors: Aye Aung, Susanto RahardjaAbstract:A new Transform known as conjugate symmetric sequency-ordered complex Hadamard Transform (CS-SCHT) is presented in this paper. The Transform Matrix of this Transform possesses sequency ordering and the spectrum obtained by the CS-SCHT is conjugate symmetric. Some of its important properties are discussed and analyzed. Sequency defined in the CS-SCHT is interpreted as compared to frequency in the discrete Fourier Transform. The exponential form of the CS-SCHT is derived, and the proof of the dyadic shift invariant property of the CS-SCHT is also given. The fast and efficient algorithm to compute the CS-SCHT is developed using the sparse Matrix factorization method and its computational load is examined as compared to that of the SCHT. The applications of the CS-SCHT in spectrum estimation and image compression are discussed. The simulation results reveal that the CS-SCHT is promising to be employed in such applications.
Nabila Philip Attalla Seif - One of the best experts on this subject based on the ideXlab platform.
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hermite gaussian like eigenvectors of the discrete fourier Transform Matrix based on the direct utilization of the orthogonal projection matrices on its eigenspaces
IEEE Transactions on Signal Processing, 2006Co-Authors: M T Hanna, Nabila Philip Attalla Seif, Waleed A AhmedAbstract:A new version is proposed for the Gram-Schmidt algorithm (GSA), the orthogonal procrustes algorithm (OPA) and the sequential orthogonal procrustes algorithm (SOPA) for generating Hermite-Gaussian-like orthonormal eigenvectors for the discrete Fourier Transform Matrix F. This version is based on the direct utilization of the orthogonal projection matrices on the eigenspaces of Matrix F rather than the singular value decomposition of those matrices for the purpose of generating initial orthonormal eigenvectors. The proposed version of the algorithms has the merit of achieving a significant reduction in the computation time
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hermite gaussian like eigenvectors of the discrete fourier Transform Matrix based on the singular value decomposition of its orthogonal projection matrices
IEEE Transactions on Circuits and Systems, 2004Co-Authors: M T Hanna, Nabila Philip Attalla Seif, Waleed A AhmedAbstract:A technique is proposed for generating initial orthonormal eigenvectors of the discrete Fourier Transform Matrix F by the singular-value decomposition of its orthogonal projection matrices on its eigenspaces and efficiently computable expressions for those matrices are derived. In order to generate Hermite-Gaussian-like orthonormal eigenvectors of F given the initial ones, a new method called the sequential orthogonal procrustes algorithm (SOPA) is presented based on the sequential generation of the columns of a unitary Matrix rather than the batch evaluation of that Matrix as in the OPA. It is proved that for any of the SOPA, the OPA, or the Gram-Schmidt algorithm (GSA) the output Hermite-Gaussian-like orthonormal eigenvectors are invariant under the change of the input initial orthonormal eigenvectors.
Aye Aung - One of the best experts on this subject based on the ideXlab platform.
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a robust watermarking scheme using sequency ordered complex hadamard Transform
Signal Processing Systems, 2011Co-Authors: Aye Aung, Susanto RahardjaAbstract:This paper presents a robust phase watermarking scheme for still digital images based on the sequency-ordered complex Hadamard Transform (SCHT). The Transform Matrix of the SCHT exhibits sequency ordering which is analogous to frequency in the discrete Fourier Transform (DFT). Hence, sequency-based image analysis can be performed for image watermarking while providing simple implementation and with less computational complexity for computation of the Transform. As the SCHT coefficients are complex numbers which consist of both magnitudes and phases, they are suited to adopt phase modulation techniques to embed the watermark. In this proposed scheme, the phases of the SCHT coefficients in the sequency domain are altered to convey the watermark information using the phase shift keying (PSK) modulation. Low amplitude block selection (LABS) is used to enhance the imperceptibility of digital watermark, and amplitude boost (AB) method is employed to improve the robustness of the watermarking scheme. Spread spectrum (SS) technique is adopted to increase the security of watermark against various unintentional or intentional attacks. In order to demonstrate the effectiveness of the proposed watermarking scheme, simulations are conducted under various kinds of attacking operations. The results show that the proposed scheme is able to sustain a series of attacks including common geometric Transformations such as scaling, rotating, cropping, painting, and common image-processing operations such as JPEG compression, low-pass filtering, sharpening, noising and phase perturbation, etc. Comparisons of the simulation results with the other schemes are also mentioned and the results reveal that the proposed scheme shows better robustness.
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conjugate symmetric sequency ordered complex hadamard Transform
IEEE Transactions on Signal Processing, 2009Co-Authors: Aye Aung, Susanto RahardjaAbstract:A new Transform known as conjugate symmetric sequency-ordered complex Hadamard Transform (CS-SCHT) is presented in this paper. The Transform Matrix of this Transform possesses sequency ordering and the spectrum obtained by the CS-SCHT is conjugate symmetric. Some of its important properties are discussed and analyzed. Sequency defined in the CS-SCHT is interpreted as compared to frequency in the discrete Fourier Transform. The exponential form of the CS-SCHT is derived, and the proof of the dyadic shift invariant property of the CS-SCHT is also given. The fast and efficient algorithm to compute the CS-SCHT is developed using the sparse Matrix factorization method and its computational load is examined as compared to that of the SCHT. The applications of the CS-SCHT in spectrum estimation and image compression are discussed. The simulation results reveal that the CS-SCHT is promising to be employed in such applications.
