Color information is very important in setting the style of images, but always influenced by internal and external imaging factors. For this reason, it is necessary to eliminate color inconsistency between different views in multi-view imaging. Up to now, many color transfer methods have been proposed mainly for vivid color appearance, in which the mean, variance, or covariance information are ...

We propose an Iterative Nonlinear Gaussianization Algorithm (INGA) which seeks a nonlinear map from a set of dependent random variables to independent Gaussian random variables. A direct motivation of INGA is to extend principal component analysis (PCA), which transforms a set of correlated random variables into uncorrelated (independent up to second order) random variables, and Independent Com...

OBJECTIVE Many researchers have studied automatic EEG classification and recently a lot of work has been done on artefact-removal from EEG data using independent component analyses (ICA). However, demonstrating that a ICA-processed multichannel EEG measurement becomes more interpretable compared to the raw data (as is usually done in work on ICA-processing of EEG data) does not yet prove that d...

Multi-neuronal recording is a powerful electrophysiological technique that has revealed much of what is known about the neuronal interactions in the brain. However, it is difficult to detect precise spike timings, especially synchronized simultaneous firings, among closely neighboring neurons recorded by one common electrode because spike waveforms overlap on the electrode when two or more neur...

Analysis of multi/hyperspectral imagery necessitates a selection of an optimal subset of bands in order to avoid the Hughes phenomena and parameter estimation problems due to interband correlation. This can be achieved by employing feature extraction techniques for significant reduction of data dimensionality. From the perspective of statistical pattern recognition, feature extraction refers to...

functional magnetic resonance imaging (fmri) is a safe and non-invasive way to assess brain functions by using signal changes associated with brain activity. the technique has become a ubiquitous tool in basic, clinical and cognitive neuroscience. this method can measure little metabolism changes that occur in active part of the brain. we process the fmri data to be able to find the parts of br...

CONTEXT The importance of an abnormal ionized calcium (iCa) measurement in noncritically ill patients is unclear. Furthermore, iCa monitoring is more expensive than measurement of total calcium and consumes more laboratory resources. We hypothesize that most iCa tests are ordered for routine monitoring in asymptomatic patients, and results do not influence clinical management. OBJECTIVE To ch...

Synthetic aperture radar (SAR) imaging has the characteristics of acquiring remote sensing data under all weather and all time. So SAR image change detection techniques have large advantage in abruptly natural and man-made disaster. Inherent speckle noise of SAR image badly obstructs the applications for SAR image change detection. SAR image belongs to non-Gaussian distribution in general, whic...