SHERRIFF, MARK STEPHEN. Analyzing Software Artifacts through Singular Value Decomposition to Guide Development Decisions. (Under the direction of Laurie A. Williams.) During development, programming teams will produce numerous types of software development artifacts. A software development artifact is an intermediate or final product that is the result or by-product of software development. Hid...

In this paper, a new satellite image contrast enhancement technique based on s Atrous wavelet transform and singular value decomposition (SVD) has been proposed. To obtain shift invariant discrete wavelet transform decomposition for images, we introduced the discrete wavelet transform known a “A trous” algorithm to decompose the image into wavelet planes which is computed as the difference betw...

We study k-SVD that is to obtain the first k singular vectors of a matrix A. Recently, a few breakthroughs have been discovered on k-SVD: Musco and Musco [19] proved the first gap-free convergence result using the block Krylov method, Shamir [21] discovered the first variance-reduction stochastic method, and Bhojanapalli et al. [7] provided the fastestO(nnz(A)+ poly(1/ε))-time algorithm using a...

Singular value decomposition (SVD) is a general-purpose mathematical analysis tool that has been used in a variety of information-retrieval applications. As the size and complexity of retrieval collections increase, it is crucial for our analysis tools to scale accordingly. To this end, we have studied the application of a new theoretically justiied SVD approximation algorithm to the problem of...

In this paper, we propose a novel technique for video shot segmentation and classiication based on the Singular Value Decomposition (SVD). For the input video sequence, we create a feature-frame matrix A, and perform the SVD on it. From this SVD, we are able to not only derive the reened feature space to better segment the video sequence along time axis, but also deene metrics to enable classii...

An adaptive Singular Value Decomposition (SVD) algorithm is an optimal method to obtain spatial multiplexing gain MIMO-OFDM systems. We present an orthogonal reconstruction scheme to obtain more accurate SVD outputs and then the system performance will be greatly enhanced. Moreover this project reduces high cost of implementation and high decomposing latency. Finally adaptive SVD engine is simu...

Every teacher of linear algebra should be familiar with the matrix singular value decomposition (or SVD). It has interesting and attractive algebraic properties, and conveys important geometrical and theoretical insights about linear transformations. The close connection between the SVD and the well known theory of diagonalization for symmetric matrices makes the topic immediately accessible to...

Many current watermarking algorithms insert data in the spatial or transform domains like the discrete cosine, the discrete Fourier, and the discrete wavelet transforms. In this paper, we present a data-hiding algorithm that exploits the singular value decomposition (SVD) representation of the data. We compute the SVD of the host image and the watermark and embed the watermark in the singular v...