Union is strength in lossy image compression

In this work, we present a comparison between different techniques of image compression. First, the image is divided in blocks which are organized according to a certain scan. Later, several compression techniques are applied, combined or alone. Such techniques are: wavelets (Haar's basis), Kar...

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Autor principal: Mastriani, M.
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: 2009
Acceso en línea:Registro en Scopus
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100 1 |a Mastriani, M. 
245 1 0 |a Union is strength in lossy image compression 
260 |c 2009 
270 1 0 |m Mastriani, M.; Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires Pabellón I, Intendente Güiraldes 2160, Ciudad Universitaria, (C1428EGA), Buenos Aires, Argentina; email: mmastriani@dc.uba.ar 
506 |2 openaire  |e Política editorial 
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504 |a Wien, M., (2004) Variable Block-Size Transforms for Hybrid Video Coding, , Degree Thesis, Institut für Nachrichtentechnik der Rheinisch-Westfälischen Technischen Hchschule Aachen, February 
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504 |a Mastriani, M., Giraldez, A., Smoothing of coefficients in wavelet domain for speckle reduction in Synthetic Aperture Radar images (2005) ICGST International Journal on Graphics, 6, pp. 1-8. , Vision and Image Processing (GVIP) 
504 |a Mastriani, M., Giraldez, A., Despeckling of SAR images in wavelet domain (2005) GIS Development Magazine, 9 (9), pp. 38-40. , Sept 
504 |a Mastriani, M., Giraldez, A., Microarrays denoising via smoothing of coefficients in wavelet domain (2005) WSEAS Transactions on Biology and Biomedicine 
504 |a Mastriani, M., Giraldez, A., Fuzzy thresholding in wavelet domain for speckle reduction in Synthetic Aperture Radar images (2005) ICGST International on Journal of Artificial Intelligence and Machine Learning, 5 
504 |a Mastriani, M., Denoising based on wavelets and deblurring via selforganizing map for Synthetic Aperture Radar images (2005) ICGST International on Journal of Artificial Intelligence and Machine Learning, 5 
504 |a Mastriani, M., Systholic Boolean Orthonormalizer Network in Wavelet Domain for Microarray Denoising (2005) ICGST International Journal on Bioinformatics and Medical Engineering, 5 
504 |a Mastriani, M., Denoising based on wavelets and deblurring via selforganizing map for Synthetic Aperture Radar images (2005) International Journal of Signal Processing, 2 (4), pp. 226-235 
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504 |a Mastriani, M., Giraldez, A., Microarrays denoising via smoothing of coefficients in wavelet domain (2006) International Journal of Biomedical Sciences, 1 (1), pp. 7-14 
504 |a Mastriani, M., Giraldez, A., Kalman' Shrinkage for Wavelet-Based Despeckling of SAR Images (2006) International Journal of Intelligent Systems and Technologies, 1 (3), pp. 190-196 
504 |a Mastriani, M., Giraldez, A., Neural Shrinkage for Wavelet-Based SAR Despeckling (2006) International Journal of Systems and Technologies, 1 (3), pp. 211-222 
504 |a Mastriani, M., Fuzzy Thresholding in Wavelet Domain for Speckle Reduction in Synthetic Aperture Radar Images (2006) International Journal of Systems and Technologies, 1 (3), pp. 252-265 
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520 3 |a In this work, we present a comparison between different techniques of image compression. First, the image is divided in blocks which are organized according to a certain scan. Later, several compression techniques are applied, combined or alone. Such techniques are: wavelets (Haar's basis), Karhunen-Loève Transform, etc. Simulations show that the combined versions are the best, with minor Mean Squared Error (MSE), and higher Peak Signal to Noise Ratio (PSNR) and better image quality, even in the presence of noise.  |l eng 
593 |a Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires Pabellón I, Intendente Güiraldes 2160, Ciudad Universitaria, (C1428EGA), Buenos Aires, Argentina 
690 1 0 |a HAAR'S BASIS 
690 1 0 |a IMAGE COMPRESSION 
690 1 0 |a KARHUNEN-LOÈVE TRANSFORM 
690 1 0 |a MORTON'S SCAN 
690 1 0 |a ROW-RAFTER SCAN 
690 1 0 |a COMPRESSION TECHNIQUES 
690 1 0 |a HAAR'S BASIS 
690 1 0 |a LOSSY IMAGE COMPRESSION 
690 1 0 |a MEAN SQUARED ERROR 
690 1 0 |a MORTON'S SCAN 
690 1 0 |a PEAK SIGNAL TO NOISE RATIO 
690 1 0 |a ROW-RAFTER SCAN 
690 1 0 |a ENGINEERING 
690 1 0 |a TECHNOLOGY 
690 1 0 |a IMAGE COMPRESSION 
773 0 |d 2009  |g v. 35  |h pp. 704-721  |p World Acad. Sci. Eng. Technol.  |x 2010376X  |t World Academy of Science, Engineering and Technology 
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