Journal ArticleDOI
Combined techniques of singular value decomposition and vector quantization for image coding
Jar-Ferr Yang,Chiou-Liang Lu +1 more
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TLDR
In this paper, the combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding.Abstract:
The combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding. Given a codebook consisting of singular vectors, two algorithms, which find the best-fit candidates without involving the complicated SVD computation, are described. Simulation results show that the proposed methods are better than the discrete cosine transform (DCT) in terms of energy compaction, data rate, image quality, and decoding complexity. >read more
Citations
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Proceedings ArticleDOI
Robust DWT-SVD domain image watermarking: embedding data in all frequencies
Emir Ganic,Ahmet M. Eskicioglu +1 more
TL;DR: A hybrid scheme based on DWT and Singular Value Decomposition (SVD) is presented, which allows the development of a watermarking scheme that is robust to a wide range of attacks.
Journal ArticleDOI
An Efficient SVD-Based Method for Image Denoising
TL;DR: The experimental results demonstrate that the proposed method can effectively reduce noise and be competitive with the current state-of-the-art denoising algorithms in terms of both quantitative metrics and subjective visual quality.
Book ChapterDOI
Estimating the Jacobian of the Singular Value Decomposition: Theory and Applications
TL;DR: In this paper, an exact analytic technique is developed that facilitates the estimation of the Jacobian using calculations based on simple linear algebra, which is very useful in certain applications involving multivariate regression or the computation of the uncertainty related to estimates obtained through the Singular Value Decomposition.
Journal ArticleDOI
Robust embedding of visual watermarks using discrete wavelet transform and singular value decomposition
Emir Ganic,Ahmet M. Eskicioglu +1 more
TL;DR: A hybrid nonblind scheme based on DWT and singular value decomposition (SVD) is presented, and it is shown that it is considerably more robust and reliable than a pure SVD-based scheme.
Proceedings ArticleDOI
Digital image watermarking using singular value decomposition
TL;DR: Simulation results are provided which demonstrate the robustness of the proposed technique to a variety of common image degradations and the results of the approach are compared to other transform domain watermarking methods.
References
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Journal ArticleDOI
An Algorithm for Vector Quantizer Design
Y. Linde,A. Buzo,Robert M. Gray +2 more
TL;DR: An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data.
Journal ArticleDOI
Discrete Cosine Transform
TL;DR: In this article, a discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed, which can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering.
Journal Article
Vector quantization
TL;DR: During the past few years several design algorithms have been developed for a variety of vector quantizers and the performance of these codes has been studied for speech waveforms, speech linear predictive parameter vectors, images, and several simulated random processes.