Search results for "Computer Science::Computer Vision and Pattern Recognition"
showing 10 items of 193 documents
Fast, Reliable Head Tracking Under Varying Illumination
2003
An improved technique for 3D head tracking under varying illumination conditions is proposed. The head is modeled as a texture mapped cylinder. Tracking is formulated as an image registration problem in the cylinder's texture map image. To solve the registration problem in the presence of lighting variation and head motion, the residual error of registration is modeled as a linear combination of texture warping templates and orthogonal illumination templates. Fast and stable on-line tracking is then achieved via regularized weighted least squares minimization of the registration error. The regularization term tends to limit potential ambiguities that arise in the warping and illumination te…
Estimation of Evapotranspiration by Hargreaves Formula and Remotely Sensed Data in Semi-arid Mediterranean Areas
1997
Abstract A methodology is proposed for estimating evapotranspiration by Hargreaves formula and image analysis of remotely sensed data. At first, for a large sicilian basin (Belice basin), theactualevapotranspiration values are estimated by the energy balance equation, spectral data of two Landsat TM images and ground agrometereological measurements. Then theseactualevapotranspiration estimates and thereferenceevapotranspiration values obtained by a slightly modified Hargreaves formula, which incorporates the outgoing short-wave radiation and an albedo coefficient equal to 0·23, are used for calculating suitable crop coefficients. Finally, the minimum area of each land-use map unit, obtained…
Hypergraph imaging: an overview
2002
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…
Quantitative comparison of new image processing methods for volumetric analysis of left ventricular contrast echocardiograms
2003
An effort has been made to develop image processing methods which allow a definite and precise tracking of the borderline of the ventricle in two-dimensional echocardiograms. Experience is reported with two new methods, which are based on the gray-level rise (GL) and the signal-to-noise ratio (SNR) in combined heart-phase-triggered image series. A quantitative comparison of these time-series methods is presented with respect to the interpretation of a single native image (noncontrast image), a single contrast-material image, the corresponding subtraction image, and the corresponding color superposition image. The comparison is based on the calculation of the ejection fraction using the abov…
Multi-resolution spatial unmixing for MERIS and Landsat image fusion
2016
Nowadays, the increasing quantity of applications using images from Earth Observation satellites makes demanding better spatial, spectral and temporal resolutions. Nevertheless, due to the technical constraint of a trade off between spatial and spectral resolutions, and between spatial resolution and coverage, high spatial resolution is related with low spectral and temporal resolutions and vice versa. Data fusion methods are a good solution to combine information from multiple sensors in order to obtain image products with better characteristics. In this paper, we propose an image fusion approach based on a multi-resolution and multi-source unmixing. The proposed methodology yields a compo…
Improved multi-resolution image fusion
2005
This work describes an automatic technique able to fuse different images of the same scene, acquired at different settings, in order to obtain an enhanced single representation of the scene of interest by an improved picture fusion scheme. This allows the extending of the functionalities (depth of field, dynamic range) of medium and low cost digital cameras. When multi-scale decomposition is used on multi-focused images, magnification effects of the lens focusing system cause an incorrect estimation of all pixels in the final image. In our approach new techniques able to reduce these artifacts are introduced. The algorithm has been applied both on full RGB and on color filter array (CFA) im…
Diffusion equations with negentropy applied to denoise mammographic images.
2006
Mammography is a radiographic technique used for the detection of breast lesions. The analysis of the digital image normally requires a previous application of filters as a preprocessing step to reduce the noise level of the image, while preserving important details to carry out a suitable diagnostic. In the literature, there are a large amount of denoising techniques applied to different medical images. In this work we have studied the performance of a diffusive filter with a stopping condition based on the statistical concept of negentropy, applied to denoise mammographic images. The negentropy has been succesfully prove with other denoising methods as independent component analysis by th…
Combining fuzzy C-mean and normalized convolution for cloud detection in IR images
2009
An important task for the cloud monitoring in several frameworks is providing maps of the cloud coverage. In this paper we present a method to detect cloudy pixels for images taken from ground by an infra-red camera. The method is a three-steps algorithm mainly based on a Fuzzy C-Mean clustering, that works on a feature space derived from the original image and the output of the reconstructed image obtained via normalized convolution. Experiments, run on several infra-red images acquired under different conditions, show that the cloud maps returned are satisfactory. © 2009 Springer Berlin Heidelberg.
Three-dimensional polarimetric computational integral imaging
2012
In this paper, we propose a novel 3D polarimetric computational integral imaging system by using polarization diversity of objects under natural illumination conditions. In the system, the measured Stokes polarization parameters are utilized to generate degree of polarization images of a 3D scene. Based on degree of polarization images and original 2D images, we utilize a modified computational reconstruction method to perform 3D polarimetric image reconstruction. The system may be used to detect or classify objects with distinct polarization signatures in 3D space. Experimental results also show the proposed system may mitigate the effect of occlusion in 3D reconstruction.
Relay optics for enhanced integral imaging
2007
Integral imaging provides with three-dimensional (3D) images. This technique works perfectly with incoherent light and does not need the use of any special glasses nor stabilization techniques. Here we present relay systems for both acquire and display 3D images. Some other important challenges are revisited.