Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales
This paper shows and explains the process implemented for the development of feed- forward neural networks with the aim of compress digital image color. It sets oul sorne traditional techniques and develops tvvo topologies to implement feed forward. During the development of networks, fue items that...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universidad de Antioquia
2012-01-01
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| Series: | Revista Facultad de Ingeniería Universidad de Antioquia |
| Subjects: | |
| Online Access: | http://www.redalyc.org/articulo.oa?id=43025803006 |
| _version_ | 1797723619218948096 |
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| author | Andrés Eduardo Gaona Barrera Néstor Andrés Lugo Currea Álvaro Fernando Roldán Hernández |
| author_facet | Andrés Eduardo Gaona Barrera Néstor Andrés Lugo Currea Álvaro Fernando Roldán Hernández |
| author_sort | Andrés Eduardo Gaona Barrera |
| collection | DOAJ |
| description | This paper shows and explains the process implemented for the development of feed- forward neural networks with the aim of compress digital image color. It sets oul sorne traditional techniques and develops tvvo topologies to implement feed forward. During the development of networks, fue items that are considered: number of layers, number of neurons, image type, size and munber of blocks to train, to optimize performance during final training. It also discusses the standard quality of the image obtained, as peak signal noise relation (PSNR) and cornpression, which typically obtain values above 35dB in terms of PSNR and 2 bits per pixel in gray or 3 bpp color images, with maximum time of 3 seconds for images less than I mega pixel. Finally out some dravvbacks and presents conclusions of this type of compression. |
| first_indexed | 2024-03-12T10:04:21Z |
| format | Article |
| id | doaj.art-62f54f791a3149d491fb5f6061d2f945 |
| institution | Directory Open Access Journal |
| issn | 0120-6230 2422-2844 |
| language | English |
| last_indexed | 2024-03-12T10:04:21Z |
| publishDate | 2012-01-01 |
| publisher | Universidad de Antioquia |
| record_format | Article |
| series | Revista Facultad de Ingeniería Universidad de Antioquia |
| spelling | doaj.art-62f54f791a3149d491fb5f6061d2f9452023-09-02T11:22:41ZengUniversidad de AntioquiaRevista Facultad de Ingeniería Universidad de Antioquia0120-62302422-28442012-01-01658598Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitalesAndrés Eduardo Gaona BarreraNéstor Andrés Lugo CurreaÁlvaro Fernando Roldán HernándezThis paper shows and explains the process implemented for the development of feed- forward neural networks with the aim of compress digital image color. It sets oul sorne traditional techniques and develops tvvo topologies to implement feed forward. During the development of networks, fue items that are considered: number of layers, number of neurons, image type, size and munber of blocks to train, to optimize performance during final training. It also discusses the standard quality of the image obtained, as peak signal noise relation (PSNR) and cornpression, which typically obtain values above 35dB in terms of PSNR and 2 bits per pixel in gray or 3 bpp color images, with maximum time of 3 seconds for images less than I mega pixel. Finally out some dravvbacks and presents conclusions of this type of compression.http://www.redalyc.org/articulo.oa?id=43025803006compression ratedigital image compressionlossy compressionfeedforward neural networkspeak signal noise relation |
| spellingShingle | Andrés Eduardo Gaona Barrera Néstor Andrés Lugo Currea Álvaro Fernando Roldán Hernández Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales Revista Facultad de Ingeniería Universidad de Antioquia compression rate digital image compression lossy compression feedforward neural networks peak signal noise relation |
| title | Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales |
| title_full | Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales |
| title_fullStr | Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales |
| title_full_unstemmed | Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales |
| title_short | Estudio de dos estructuras neuronales feedforward para la compresión de imágenes digitales |
| title_sort | estudio de dos estructuras neuronales feedforward para la compresion de imagenes digitales |
| topic | compression rate digital image compression lossy compression feedforward neural networks peak signal noise relation |
| url | http://www.redalyc.org/articulo.oa?id=43025803006 |
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