This is a conceptual presentation of video watermarking technique using SVD transform. SVD is sufficient and the most optimal in a given image. It is packed with energy in a given number of transformation coefficients are maximized and is easy to calculate. A method of watermarking embedding and extraction is used in this paper. Investigation of the video using SVD will give good results. The o...

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...

Singular-value decomposition (SVD)-based multiple-input multiple-output (MIMO) systems have attracted a lot of attention in the wireless community. However, applying SVD to frequency-selective MIMO channels results in unequally weighted single-input single-output (SISO) channels requiring complex resource allocation techniques for optimizing the channel performance. Therefore, a different appro...

With the rapid growth of network multimedia systems and other numerical technologies, images, audio, text and video can be more easily produced, processed as well as stored by digital devices in recent years. To conceal data in transmitting message for copyright protection the secret is very important. Various Digital Watermarking Techniques are developed to protect the secret data. This paper ...

It is possible for Singular Value Decomposition (SVD) watermark embedding to have a quasi-one-way functionality. While basic SVD embedding has the drawback of being non-reversible, an advanced SVD method which uses a reversible relation only works one-way. When embedding takes place, the decomposing matrix obtained from the original image differs from the one obtained from the embedded image. T...

The text retrieval method using Latent Semantic Indexing (LSI) with the truncated Singular Value Decomposition (SVD) has been intensively studied in recent years. The term-document matrices after SVD are full matrices, although the rank is reduced substantially. To reduce memory consumption, we examine some strategies to sparsify the truncated SVD matrices. After applying the sparsification str...

BACKGROUND AND PURPOSE The role of athersclerosis in the difference between the pathogenesis of large-vessel disease (LVD) and small-vessel disease (SVD) is a matter of debate. Common carotid artery intima-media thickness (CCA IMT) is a marker of atherosclerosis. Our aim was to compare CCA IMT between SVD and LVD patients. METHODS Two independent observers classified ischemic stroke or transi...

The blood-brain barrier protects brain tissue from potentially harmful plasma components. Small vessel disease (SVD; also termed arteriolosclerosis) is common in the brains of older people and is associated with lacunar infarcts, leukoaraiosis, and vascular dementia. To determine whether plasma extravasation is associated with SVD, we immunolabeled the plasma proteins fibrinogen and immunoglobu...

Subcortical vascular dementia (SVD) is a form of vascular dementia from small vessel disease with white matter lesions and lacunes. We hypothesized that hemodynamic and metabolic changes in the cortex during a simple motor task may reflect the impaired neurovascular coupling in SVD. We used fMRI and near-infrared spectroscopy (NIRS) simultaneously, which together provided multiple hemodynamic r...

BACKGROUND cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment (VCI). Despite this, there is a paucity of rapid simple screening tools to identify cognitive impairment in SVD and differentiate it from other common dementia types. OBJECTIVE to validate a new screening test for cognitive impairment in SVD, the Brief Memory and Executive Test (BMET) batt...