Search results for "Component analysis"
showing 10 items of 562 documents
Complex-Valued Independent Component Analysis of Natural Images
2011
Linear independent component analysis (ICA) learns simple cell receptive fields fromnatural images. Here,we showthat linear complex-valued ICA learns complex cell properties from Fourier-transformed natural images, i.e. two Gabor-like filters with quadrature-phase relationship. Conventional methods for complex-valued ICA assume that the phases of the output signals have uniform distribution. We show here that for natural images the phase distributions are, however, often far from uniform. We thus relax the uniformity assumption and model also the phase of the sources in complex-valued ICA. Compared to the original complex ICA model, the new model provides a better fit to the data, and leads…
Técnicas de análisis de posproceso en resonancia magnetica parael estudio de la conectividad cerebral
2011
Brain connectivity is a key concept for understanding brain function. Current methods to detect and quantify different types of connectivity with neuroimaging techniques are fundamental for understanding the pathophysiology of many neurologic and psychiatric disorders. This article aims to present a critical review of the magnetic resonance imaging techniques used to measure brain connectivity within the context of the Human Connectome Project. We review techniques used to measure: a) structural connectivity b) functional connectivity (main component analysis, independent component analysis, seed voxel, meta-analysis), and c) effective connectivity (psychophysiological interactions, causal …
Distribution patterns of particulate trace metals in the water column and nepheloid layer of the Gulf of Riga.
2004
The dynamics (fate) of trace metals in suspended particulate matter within the Gulf of Riga has not yet been adequately addressed in the scientific literature. Therefore, during a two year period (2001-2002) samples of suspended particulate matter and surface sediments for trace metal analysis were collected in the Gulf of Riga and the Daugava river, and these data were combined with background information from the national marine monitoring program in Latvia. This paper presents a descriptive study of solid phase trace metals (aluminium, iron, cadmium, chromium, copper, manganese, nickel, lead and zinc) dynamics and their spatial distribution within the Gulf of Riga based on Principal Comp…
Application of daily rainfall principal component analysis to the assessment of the rainy season characteristics in Senegal
2003
The interannual variability of the onset and cessation dates of the rainy season (RS) in Senegal is analyzed over the 43 yr period 1950-1992, using daily rainfall data for 34 stations. The use of principal component analysis, based on rainfall only, is explored to identify aggregate, regional indexes for the onset and cessation of the rains. The minimum and maximum values of the cumula- tive scores of principal component 1, for each year, are used to locate the onset and cessation dates, respectively. Very distinct spatial rainfall patterns are found before and after the onset/cessation dates. Mean dates compare favorably with those based on other definitions, though our method is not meant…
Elemental fingerprint of wines from the protected designation of origin Valencia
2009
Abstract Inductively coupled plasma optical emission (ICP-OES), in combination with different chemometric approaches, has been used to verify the origin of different red wine samples from Utiel-Requena, Jumilla, Yecla and Valencia protected designation of origin (PDO). The ability of multivariate analysis methods, such as hierarchical cluster analysis (HCA), principal component analysis (PCA), classification and regression trees (CARTs) and discriminant analysis (DA), to achieve wine classification from their elemental contents has been investigated. The calculations were performed using 38 variables (contents of Al, Ba, Be, Ca, Cd, Ce, Co, Cr, Cu, Dy, Er, Eu, Fe, Gd, Ho, K, La, Li, Lu, Mg,…
Multiple Mean Models of Statistical Shape and Probability Priors for Automatic Prostate Segmentation
2011
International audience; Low contrast of the prostate gland, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow regions, speckle and significant variations in prostate shape, size and in- ter dataset contrast in Trans Rectal Ultrasound (TRUS) images challenge computer aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose a probabilistic framework for automatic initialization and propagation of multiple mean parametric models derived from principal component analysis of shape and posterior probability information of the prostate region to segment the prostate. Unlike traditional statistical models of shape and int…
Spatially variant dimensionality reduction for the visualization of multi/hyperspectral images
2011
International audience; In this paper, we introduce a new approach for color visu- alization of multi/hyperspectral images. Unlike traditional methods, we propose to operate a local analysis instead of considering that all the pixels are part of the same population. It takes a segmentation map as an input and then achieves a dimensionality reduction adaptively inside each class of pixels. Moreover, in order to avoid unappealing discon- tinuities between regions, we propose to make use of a set of distance transform maps to weigh the mapping applied to each pixel with regard to its relative location with classes' centroids. Results on two hyperspec- tral datasets illustrate the efficiency of…
Parameter-free adaptive step-size multiobjective optimization applied to remote photoplethysmography
2018
International audience; In this work, we propose to reformulate the objective function of Independent Component Analysis (ICA) to make it a better posed problem in the context of Remote photoplethysmography (rPPG). In recent previous works, linear combination coefficients of RGB channels are estimated maximizing the non-Gaussianity of ICA output components. However, in the context of rPPG a priori knowledge of the pulse signal can be incorporated into the component extraction algorithm. To this end, the contrast function of regular ICA is extended with a measure of periodicity formulated using autocorrelation. This novel semi-blind source extraction method for measuring rPPG has the interes…
Source separation on hyperspectral cube applied to dermatology
2010
International audience; This paper proposes a method of quantification of the components underlying the human skin that are supposed to be responsible for the effective reflectance spectrum of the skin over the visible wavelength. The method is based on independent component analysis assuming that the epidermal melanin and the dermal haemoglobin absorbance spectra are independent of each other. The method extracts the source spectra that correspond to the ideal absorbance spectra of melanin and haemoglobin. The noisy melanin spectrum is fixed using a polynomial fit and the quantifications associated with it are reestimated. The results produce feasible quantifications of each source compone…
LDR Image to HDR Image Mapping with Overexposure Preprocessing
2013
International audience; Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we . present a new,LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principl…