Synopsis
Applications, which need to store large database and/or transmit digital images requiring high bit-rates over channels with limited bandwidth, have demanded improved image compression techniques.. Encoding an image into fewer bits is useful in reducing the storage requirements in image archival systems, or in decreasing the bandwidth for image transmission. In standard image compression methods (e.g. JPEG), as the bits per pixel reduces, the picture quality deteriorates because of the use of bigger quantization step size. In this work, image compression techniques are designed keeping in mind the human visual system. Practical and effective image compression system based on Neuro-Wavelet models have been proposed which combines the advantages of neural network and wavelet transform with vector quantization. Fuzzy c-means and Fuzzy vector quantization algorithms have also been used to make use of uncertainty for the benefit of the clustering process. We have compared the performances of different clustering algorithms applied to the proposed encoder. Experimental results on real images of varying complexity have established the robustness and effectiveness of the method
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About the Author
Dr. Vipula Singh has obtained her PhD in Information Technology in 2009. She is working as a professor. She is the author of several articles published in reputed journals and is a member of different international professional bodies. Her areas of research are image processing, pattern recignition and neural networks.
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Development of Image Compression Compression Algorithms
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Applications, which need to store large database and/or transmit digital images requiring high bit-rates over channels with limited bandwidth, have demanded improved image compression techniques. Encoding an image into fewer bits is useful in reducing the storage requirements in image archival systems, or in decreasing the bandwidth for image transmission. In standard image compression methods (e.g. JPEG), as the bits per pixel reduces, the picture quality deteriorates because of the use of bigger quantization step size. In this work, image compression techniques are designed keeping in mind the human visual system. Practical and effective image compression system based on Neuro-Wavelet models have been proposed which combines the advantages of neural network and wavelet transform with vector quantization. Fuzzy c-means and Fuzzy vector quantization algorithms have also been used to make use of uncertainty for the benefit of the clustering process. We have compared the performances of different clustering algorithms applied to the proposed encoder. Experimental results on real images of varying complexity have established the robustness and effectiveness of the method 172 pp. Englisch. Seller Inventory # 9783845436319
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Development of Image Compression Algorithms
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh VipulaDr. Vipula Singh has obtained her PhD in Information Technology in 2009. She is working as a professor. She is the author of several articles published in reputed journals and is a member of different international profes. Seller Inventory # 5482484
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Development of Image Compression Compression Algorithms | Using Soft Computing Techniques
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Taschenbuch. Condition: Neu. Development of Image Compression Compression Algorithms | Using Soft Computing Techniques | Vipula Singh (u. a.) | Taschenbuch | 172 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845436319 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 106819265
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Development of Image Compression Compression Algorithms
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Applications, which need to store large database and/or transmit digital images requiring high bit-rates over channels with limited bandwidth, have demanded improved image compression techniques. Encoding an image into fewer bits is useful in reducing the storage requirements in image archival systems, or in decreasing the bandwidth for image transmission. In standard image compression methods (e.g. JPEG), as the bits per pixel reduces, the picture quality deteriorates because of the use of bigger quantization step size. In this work, image compression techniques are designed keeping in mind the human visual system. Practical and effective image compression system based on Neuro-Wavelet models have been proposed which combines the advantages of neural network and wavelet transform with vector quantization. Fuzzy c-means and Fuzzy vector quantization algorithms have also been used to make use of uncertainty for the benefit of the clustering process. We have compared the performances of different clustering algorithms applied to the proposed encoder. Experimental results on real images of varying complexity have established the robustness and effectiveness of the methodVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch. Seller Inventory # 9783845436319
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Development of Image Compression Compression Algorithms : Using Soft Computing Techniques
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Applications, which need to store large database and/or transmit digital images requiring high bit-rates over channels with limited bandwidth, have demanded improved image compression techniques. Encoding an image into fewer bits is useful in reducing the storage requirements in image archival systems, or in decreasing the bandwidth for image transmission. In standard image compression methods (e.g. JPEG), as the bits per pixel reduces, the picture quality deteriorates because of the use of bigger quantization step size. In this work, image compression techniques are designed keeping in mind the human visual system. Practical and effective image compression system based on Neuro-Wavelet models have been proposed which combines the advantages of neural network and wavelet transform with vector quantization. Fuzzy c-means and Fuzzy vector quantization algorithms have also been used to make use of uncertainty for the benefit of the clustering process. We have compared the performances of different clustering algorithms applied to the proposed encoder. Experimental results on real images of varying complexity have established the robustness and effectiveness of the method. Seller Inventory # 9783845436319
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Development of Image Compression Algorithms: Using Soft Computing Techniques
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