Preliminary Study on the Feasibility of Performing Quantitative Precipitation Estimation Using X-band Radar

IRCTR has built an experimental X-band Doppler po-larimetric weather radar system aimed at obtaining high temporal and spatial resolution measurements of precipitation, with particular interest in light rain and drizzle. In this paper a first analysis of the feasibility of obtaining accurate quantitative precipitation estimation from the radar data performed using a high density network of rain gauges is presented

Sparse image approximation with application to flexible image coding

Natural images are often modeled through piecewise-smooth regions. Region edges, which correspond to the contours of the objects, become, in this model, the main information of the signal. Contours have the property of being smooth functions along the direction of the edge, and irregularities on the perpendicular direction. Modeling edges with the minimum possible number of terms is of key importance for numerous applications, such as image coding, segmentation or denoising. Standard separable basis fail to provide sparse enough representation of contours, due to the fact that this kind of basis do not see the regularity of edges. In order to be able to detect this regularity, a new method based on (possibly redundant) sets of basis functions able to capture the geometry of images is needed. This thesis presents, in a first stage, a study about the features that basis functions should have in order to provide sparse representations of a piecewise-smooth image. This study emphasizes the need for edge-adapted basis functions, capable to accurately capture local orientation and anisotropic scaling of image structures. The need of different anisotropy degrees and orientations in the basis function set leads to the use of redundant dictionaries. However, redundant dictionaries have the inconvenience of giving no unique sparse image decompositions, and from all the possible decompositions of a signal in a redundant dictionary, just the sparsest is needed. There are several algorithms that allow to find sparse decompositions over redundant dictionaries, but most of these algorithms do not always guarantee that the optimal approximation has been recovered. To cope with this problem, a mathematical study about the properties of sparse approximations is performed. From this, a test to check whether a given sparse approximation is the sparsest is provided. The second part of this thesis presents a novel image approximation scheme, based on the use of a redundant dictionary. This scheme allows to have a good approximation of an image with a number of terms much smaller than the dimension of the signal. This novel approximation scheme is based on a dictionary formed by a combination of anisotropically refined and rotated wavelet-like mother functions and Gaussians. An efficient Full Search Matching Pursuit algorithm to perform the image decomposition in such a dictionary is designed. Finally, a geometric image coding scheme based on the image approximated over the anisotropic and rotated dictionary of basis functions is designed. The coding performances of this dictionary are studied. Coefficient quantization appears to be of crucial importance in the design of a Matching Pursuit based coding scheme. Thus, a quantization scheme for the MP coefficients has been designed, based on the theoretical energy upper bound of the MP algorithm and the empirical observations of the coefficient distribution and evolution. Thanks to this quantization, our image coder provides low to medium bit-rate image approximations, while it allows for on the fly resolution switching and several other affine image transformations to be performed directly in the transformed domain

Matching Pursuit through Genetic Algorithms

Matching Pursuit is a greedy algorithmthat decomposes any signal into a linear expansion of waveforms taken from a redundant dictionary. Computing the projection of the signal on every element of the basis has a high computational cost. To reduce this computational cost, optimized computational error minimization methods have to be found. Genetic Algorithms have shown to be a good tool to this approach

R-D Analysis of Adaptive Edge Representations

This paper presents a Rate-Distortion analysis for a simple horizon edge image model. A quadtree with anisotropy and rotation is performed on this kind of image, giving a toy model for a non-linear adaptive coding technique, and its Rate-Distortion behavior is studied. The effect of refining the quadtree decomposition is also analyzed

Evolutionary Multiresolution Matching Pursuit and its Relations with the Human Visual System

This paper proposes a multiresolution Matching Pursuit decomposition of natural images. Matching Pursuit is a greedy algorithm that decomposes any signal into a linear expansion of waveforms taken from a redundant dictionary, by iteratively picking the waveform that best matches the input signal. Since the computational cost rapidly grows with the size of the signal, we propose a multiresolution strategy that, together with an efficient dictionary, significantly reduces the encoding complexity while still providing an efficient representation. Such a decomposition is perceptually very effective at low bit rate coding, thanks to similiarities with the Human Visual System information processing

High flexibility scalable image coding

This paper presents a new, highly flexible, scalable image coder based on a Matching Pursuit expansion. The dictionary of atoms is built by translation, rotation and anisotropic refinement of gaussian functions, in order to efficiently capture edges in natural images. In the same time, the dictionary is invariant under isotropic scaling, which interestingly leads to very simple spatial resizing operations. It is shown that the proposed scheme compares to state-of-the-art coders when the compressed image is transcoded to a lower (octave-based) spatial resolution. In contrary to common compression formats, our bit-stream can moreover easily and efficiently be decoded at any spatial resolution, even with irrational re-scaling factors. In the same time, the Matching Pursuit algorithm provides an intrinsically progressive stream. This worthy feature allows for easy rate filtering operations, where the least important atoms are simply discarded to fit restrictive bandwidth constraints. Our scheme is finally shown to favorably compare to state-of-the-art progressive coders for moderate to quite important rate reductions

A generalized Rate-Distortion limit for edge representation

This paper presents a rate-distortion analysis for a simple horizon edge image model. A quadtree with anisotropy and rotation is performed in this kind of image, giving a toy model for a non-linear adaptive coding technique, and its rate-distortion behavior is studied. The effect of refining the quadtree decomposition in the Rate-Distortion decay is also studied

An improved decoding scheme for Matching Pursuit Streams

This work presents an improved coefficient decoding method for Matching Pursuit streams. It builds on the adaptive a posteriori quantization of coefficients, and implements an interpolation scheme that enhances the inverse quantization performance at the decoder. A class of interpolation functions is introduced, that capture the behavior of coefficients after conditional scalar quantization. The accuracy of the interpolation scheme is verified experimentally, and the novel decoding algorithm is further evaluated in image coding applications. It can be seen that the proposed method improves the rate-distortion performance by up to 0.5 dB, only by changing the reconstruction strategy at the decoder

Investigació de contaminants orgànics en aigües de Catalunya

Les anàlisis de la fracció orgànica no volàtil de l'aigua de Barcelona, que representa almenys el 80 % de l'extret orgànic total, han estat realitzades mitjançant fraccionament per HPLC i caracteritzacifió per FAB-CID-MIKES. Hom ha assajat també 1'acoblament HPLC/EM. Els resultats obtinguts marquen un camí adient per a la identificació de compostos en barreges complexes. Entre els compostos no volàtils identificats han estat trobats detergents no iònics, aviònics i poliglicols. FAB i FAB-CID-MIKES representa una tècnica nova i complementària a l'acoblament CG/EM rutinàriament emprada al nostre laboratori. A més a més, horn duu a terme els diferents tests de genotoxicitat corn el SOS-chromtest i Ames de les diverses fraccions obtingudes per HPLC, a fi i efecte de conèixer la genotoxicitat potencial de l'aigua.Analysis of the non volatile organic fraction of Barcelona's raw water, that amounting at least 80 % of the total organic extract, have been perfomed using HPLC fractionation and FAB-CID-MIKES characterisation. LC/MS also has been evaluated. The results obtained show a promising way to the identification of components in organic complex mixtures. Among identified non volatile compounds there are no-ionic and anionic surfactants and polyglycols. FAB and FAB-CID-MIKES are becoming new and complementary techniques to routinely employed GC/MS in our laboratory. Moreover, mutagenicity tests, such as SOS chromtest and Ames, are being performed with different HPLC fractions in order to know the potential genotoxicity of water

Color Image Scalable Coding with Matching Pursuit

This paper presents a new scalable and highly flexible color image coder based on a Matching Pursuit expansion. The Matching Pursuit algorithm provides an intrinsically progressive stream and the proposed coder allows us to reconstruct color information from the first bit received. In order to efficiently capture edges in natural images, the dictionary of atoms is built by translation, rotation and anisotropic refinement of a wavelet-like mother function. This dictionary is moreover invariant under shifts and isotropic scaling, thus leading to very simple spatial resizing operations. This flexibility and adaptivity of the MP coder makes it appropriate for asymmetric applications with heterogeneous end user terminals