31 research outputs found

    High Dynamic Range Imaging by Perceptual Logarithmic Exposure Merging

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    In this paper we emphasize a similarity between the Logarithmic-Type Image Processing (LTIP) model and the Naka-Rushton model of the Human Visual System (HVS). LTIP is a derivation of the Logarithmic Image Processing (LIP), which further replaces the logarithmic function with a ratio of polynomial functions. Based on this similarity, we show that it is possible to present an unifying framework for the High Dynamic Range (HDR) imaging problem, namely that performing exposure merging under the LTIP model is equivalent to standard irradiance map fusion. The resulting HDR algorithm is shown to provide high quality in both subjective and objective evaluations.Comment: 14 pages 8 figures. Accepted at AMCS journa

    Pandora: Description of a Painting Database for Art Movement Recognition with Baselines and Perspectives

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    To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.Comment: 11 pages, 1 figure, 6 table

    Antibacterial efficacy of azithromycin with ureaplasma urealyticum in urinari infection

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    Secţia Urologie al SCAMU Catedra Microbiologie, Virusologie şi Imunologie USMF ”N.Testemitanu”In the study participated the patients, suffered of urinary infection with ureaplasma urealiticum. Aim of our study was to appreciate clinical manifestations, and determination of the efficiency of antibacterial treatment with Azithromycin in urinary disease. The treatment with Azithromycin shows benefits in urinary manifestations, decreasing the levels of specific Mycoplasma immunoglobulins and positive dynamics in humoral immunity. În cadrul studiului au participat pacienţi, care au fost diagnosticaţi cu infecţii urinare provocate de Ureaplasma urealiticum. Scopul studiului a fost de a aprecia manifestările clinice, şi de a determina eficienţa tratamentului antibacterian cu azitromicină în patologia urinară. Tratamentul cu azitromicină a condus la îmbunătăţirea stării pacienţilor, scăderea nivelului de imunoglobuline specifice şi dinamică pozitivă în imunitatea umorală

    A Parametric Logarithmic Image Processing Framework Based on Fuzzy Graylevel Accumulation by the Hamacher T-Conorm

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    It has been proven that Logarithmic Image Processing (LIP) models provide a suitable framework for visualizing and enhancing digital images acquired by various sources. The most visible (although simplified) result of using such a model is that LIP allows the computation of graylevel addition, subtraction and multiplication with scalars within a fixed graylevel range without the use of clipping. It is claimed that a generalized LIP framework (i.e., a parameterized family of LIP models) can be constructed on the basis of the fuzzy modelling of gray level addition as an accumulation process described by the Hamacher conorm. All the existing LIP and LIP-like models are obtained as particular cases of the proposed framework in the range corresponding to real-world digital images

    High Dynamic Range Imaging by Perceptual Logarithmic Exposure Merging

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    In this paper we emphasize a similarity between the logarithmic type image processing (LTIP) model and the Naka–Rushton model of the human visual system (HVS). LTIP is a derivation of logarithmic image processing (LIP), which further replaces the logarithmic function with a ratio of polynomial functions. Based on this similarity, we show that it is possible to present a unifying framework for the high dynamic range (HDR) imaging problem, namely, that performing exposure merging under the LTIP model is equivalent to standard irradiance map fusion. The resulting HDR algorithm is shown to provide high quality in both subjective and objective evaluations
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