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Jaime Moreno, Xavier Otazu, & Maria Vanrell. (2010). Contribution of CIWaM in JPEG2000 Quantization for Color Images. In Proceedings of The CREATE 2010 Conference (132–136).
Abstract: The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM(ChromaticInductionWaveletModel).
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Jaime Moreno, Xavier Otazu, & Maria Vanrell. (2010). Local Perceptual Weighting in JPEG2000 for Color Images. In 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science (255–260).
Abstract: The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM (Chromatic Induction Wavelet Model).
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Judit Martinez, Eva Costa, P. Herreros, F. Javier Sanchez, & Ramon Baldrich. (2003). A Modular and Scalable Architecture for PC-Based Real-Time Vision Systems. Real–Time Imaging, (IF: 0.512), 9, 99–112.
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A. Martinez, & Robert Benavente. (1998). The AR face database.
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Fernando Lopez, J.M. Valiente, Ramon Baldrich, & Maria Vanrell. (2005). Fast surface grading using color statistics in the CIELab space. In Pattern Recognition and Image Analysis. IbPRIA 2005 (Vol. LNCS 3523, pp. 66–673).
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Fahad Shahbaz Khan, Joost Van de Weijer, & Maria Vanrell. (2010). Who Painted this Painting? In Proceedings of The CREATE 2010 Conference (329–333).
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M. Gonzalez-Audicana, Xavier Otazu, O. Fors, & A. Seco. (2005). Comparison between Mallats and the trous discrete wavelet transform based algorithms for the fusion of multispectral and panchromatic images. International Journal of Remote Sensing, 26(3):595–614 (IF: 0.925).
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M. Gonzalez-Audicana, Xavier Otazu, O. Fors, R Garcia, & J. Nuñez. (2002). Fusion of different spatial and spectral resolution images: development, apllication and comparison of new methods based on wavelets..
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O. Fors, A. Richichi, Xavier Otazu, & J. Nuñez. (2008). A new wavelet-based approach for the automated treatment of large sets of lunar occultation data. Astronomy and Astrohysics, 297–304.
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O. Fors, Xavier Otazu, & J. Nuñez. (2001). Fusion Mediante Wavelets de Imagenes Spot-pan y del Satelite Tailandes TMSAT..
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O. Fors, J. Nuñez, Xavier Otazu, A. Prades, & Robert D. Cardinal. (2010). Improving the Ability of Image Sensors to Detect Faint Stars and Moving Objects Using Image Deconvolution Techniques. SENS - Sensors, 10(3), 1743–1752.
Abstract: Abstract: In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors.
Keywords: image processing; image deconvolution; faint stars; space debris; wavelet transform
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Robert Benavente, Maria Vanrell, & Ramon Baldrich. (2008). Parametric Fuzzy Sets for Automatic Color Naming. Journal of the Optical Society of America A, 2582–2593.
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Robert Benavente, Maria Vanrell, & Ramon Baldrich. (2006). A data set for fuzzy colour naming. Color Research & Application, 31(1):48–56.
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Robert Benavente, Maria Vanrell, & Ramon Baldrich. (2004). Estimation of Fuzzy Sets for Computational Colour Categorization. Color Research and Application, 29(5):342–353 (IF: 0.739).
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Ramon Baldrich, Maria Vanrell, Robert Benavente, & Anna Salvatella. (2003). Color Enhancement based on perceptual sharpening.
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Ramon Baldrich, Ricardo Toledo, Ernest Valveny, & Maria Vanrell. (2002). Perceptual Colour Image Segmentation..
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Agnes Borras, Francesc Tous, Josep Llados, & Maria Vanrell. (2003). High-Level Clothes Description Based on Colour-Texture and Structural Features. In 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003.
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Agnes Borras, Francesc Tous, Josep Llados, & Maria Vanrell. (2003). High-Level Clothes Description Based on Color-Texture and Structural Features. In Lecture Notes in Computer Science (Vol. 2652, 108–116).
Abstract: This work is a part of a surveillance system where content- based image retrieval is done in terms of people appearance. Given an image of a person, our work provides an automatic description of his clothing according to the colour, texture and structural composition of its garments. We present a two-stage process composed by image segmentation and a region-based interpretation. We segment an image by modelling it due to an attributed graph and applying a hybrid method that follows a split-and-merge strategy. We propose the interpretation of five cloth combinations that are modelled in a graph structure in terms of region features. The interpretation is viewed as a graph matching with an associated cost between the segmentation and the cloth models. Fi- nally, we have tested the process with a ground-truth of one hundred images.
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