This paper discussed an improvement algorithm of image digital watermarking based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). In this algorithm, a good characteristic of multiresolution and time-frequency local analysis of discrete wavelet transform combining with image intrinsic algebraic properties of SVD. After decomposing the original host image into four...

In this paper, we propose a new sampling strategy for hyperspectral signals that is based on dictionary learning and singular value decomposition (SVD). Specifically, we first learn a sparsifying dictionary from training spectral data using dictionary learning. We then perform an SVD on the dictionary and use the first few left singular vectors as the rows of the measurement matrix to obtain th...

In this paper we will first introduce the singular value decomposition (SVD) of a matrix and basic theory behind it. We will then go over the general algorithm, along with implementations in SAGE and computational efficiency comparisons with built in libraries. At the end we will discuss principal component analysis and its relation with the SVD as one of many applications.

The centroid decomposition, an approximation for the singular value decomposition (SVD), has a long history among the statistics/psychometrics community for factor analysis research. We revisit the centroid method in its original context of factor analysis and then adapt it to other than a covariance matrix. The centroid method can be cast as an O(n)-step ascent method on a hypercube. It is sho...

This paper develops an identity for additive modifications of a singular value decomposition (SVD) to reflect updates, downdates, shifts, and edits of the data matrix. This sets the stage for fast and memory-efficient sequential algorithms for tracking singular values and subspaces. In conjunction with a fast solution for the pseudo-inverse of a submatrix of an orthogonal matrix, we develop a s...

This paper proposes a novel compression combined digital image watermarking scheme based on singular value replacement technique. Image compression is achieved using Huffman encoding technique. Huffman encoding is an entropy encoding algorithm offering lossless image compression. The proposed watermarking scheme combines Integer wavelet transform (IWT) with singular value decomposition (SVD). F...

Singular Value Decomposition (SVD) is a powerful tool for multivariate analysis. However, independent computation of the SVD for each sample taken from a bandlimited matrix random process will result in singular value sample paths whose tangled evolution is not consistent with the structure of the underlying random process. The solution to this problem is developed as follows: (i) a SVD with re...

A variational formulation for the generalized singular value decomposition GSVD of a pair of matrices A R n and B R n is presented In particular a duality theory analogous to that of the SVD provides new understanding of left and right generalized singular vectors It is shown that the intersection of row spaces of A and B plays a key role in the GSVD duality theory The main result that characte...

When network and storage devices become more popular, the digital data more easily and more quickly will be distributed. Can be easily pirated copy and did not limit a large number of multimedia information (images, audio and video). Therefore, people are increasingly concerned about the protection of intellectual property rights of multimedia. Digital watermarking is a useful and the developme...