Search results for "COMPRESSION"
showing 10 items of 774 documents
Searches for heavy neutrinos from Z decays
1992
We have searched for possible fourth family heavy neutrinos, pair produced in Z0 decays, in a sample of about 112 000 hadronic Z0 final states collected with the DELPHI detector. For all mixing matrix elements we exclude a new Dirac neutrino lighter than 44.5 GeV at a 95% confidence level, if the neutrino couples to the electron or muon family, and lighter than 44.0 GeV, if the neutrino couples to the tau family. Depending on the values of the mixing element and to which lepton family the neutrino couples, we obtain mass limits up to 46.2 GeV. For all mixing matrix elements we exclude a new Majorana neutrino lighter than 39.0 GeV, if it couples to the electron or the muon family, and lighte…
Maximum likelihood difference scaling of image quality in compression-degraded images.
2007
International audience; Lossy image compression techniques allow arbitrarily high compression rates but at the price of poor image quality. We applied maximum likelihood difference scaling to evaluate image quality of nine images, each compressed via vector quantization to ten different levels, within two different color spaces, RGB and CIE 1976 L(*)a(*)b(*). In L(*)a(*)b(*) space, images could be compressed on average by 32% more than in RGB space, with little additional loss in quality. Further compression led to marked perceptual changes. Our approach permits a rapid, direct measurement of the consequences of image compression for human observers.
An evaluation framework and a benchmark for multi/hyperspectral image compression
2011
International audience; This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach (Full 3D and Hybrid). All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed…
A new minimum trees-based approach for shape matching with improved time computing : application to graphical symbols recognition
2010
Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longe…
Kolmogorov Superposition Theorem and Wavelet Decomposition for Image Compression
2009
International audience; Kolmogorov Superposition Theorem stands that any multivariate function can be decomposed into two types of monovariate functions that are called inner and external functions: each inner function is associated to one dimension and linearly combined to construct a hash-function that associates every point of a multidimensional space to a value of the real interval $[0,1]$. These intermediate values are then associated by external functions to the corresponding value of the multidimensional function. Thanks to the decomposition into monovariate functions, our goal is to apply this decomposition to images and obtain image compression. We propose a new algorithm to decomp…
Foreword for the thematic volume of the 8ISCPP. Recent advances in present and past cephalopod studies.
2012
3 pages, éditorial.; International audience
Study and Comparison of Surface Roughness Measurements
2014
Journées du Groupe de Travail en Modélisation Géométrique (GTMG'14), Lyon; This survey paper focus on recent researches whose goal is to optimize treatments on 3D meshes, thanks to a study of their surface features, and more precisely their roughness and saliency. Applications like watermarking or lossy compression can benefit from a precise roughness detection, to better hide the watermarks or quantize coarsely these areas, without altering visually the shape. Despite investigations on scale dependence leading to multi-scale approaches, an accurate roughness or pattern characterization is still lacking, but challenging for those treatments. We think there is still room for investigations t…
Compression embarquée temps réel pour caméras rapides
2005
Les caméras rapides sont de puissants outils pour étudier, par exemple, la dynamique des fluides ou le déplacement des pièces mécaniques lors d'un processus de fabrication. Nous décrivons dans ce papier, un nouveau type de caméra rapide possédant un fonctionnement original. En effet, outre le fait qu'elle utilise comme d'autres caméras, la grande flexibilité des capteurs CMOS en termes d'acquisition (ROI), elle est novatrice au niveau du transfert des données. Celles-ci pouvant être à la fois traitées et/ou compressées en temps réel au sein même de la caméra. Le transfert peut s'effectuer alors à l'aide d'une simple connection série de type USB 2.0. On réalise ainsi l'économie d'une mémoire…
Nouvelles méthodes de traitement de signaux multidimensionnels par décomposition suivant le théorème de Superposition de Kolmogorov
2010
The processing of multidimensional signal remains difficult when using monodimensional-based methods. Therefore, it is either required to extend monodimensional methods to several dimensions, which is not always possible, or to convert the multidimensional signals into 1D signals. In this case, the priority is to preserve most of the properties of the original signal. In this context, the Kolmogorov Superposition Theorem offers a promising theoretical framework for multidimensional signal conversion. In 1957, Kolmogorov demonstrated that any multivariate function can be written as sums and compositions of monovariate functions.We have focused on the image decomposition according to the supe…
Lossless and nearly-lossless image compression based on combinatorial transforms
2011
Common image compression standards are usually based on frequency transform such as Discrete Cosine Transform or Wavelets. We present a different approach for loss-less image compression, it is based on combinatorial transform. The main transform is Burrows Wheeler Transform (BWT) which tends to reorder symbols according to their following context. It becomes a promising compression approach based on contextmodelling. BWT was initially applied for text compression software such as BZIP2 ; nevertheless it has been recently applied to the image compression field. Compression scheme based on Burrows Wheeler Transform is usually lossless ; therefore we imple-ment this algorithm in medical imagi…