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Compression provides a means of reducing storage costs and increases the rate of transmission. Image compression reduces the size of graphic images without reducing image quality. Image performance is calculated using certain parameters such as PSNR (peak signal to noise ratio), CR (compression ratio), MSE (mean square error), and (BPP) per pixel bit. Mean Square error is a network performance parameter, it deals the network's Performance according to the mean of squared errors. The Peak signal to noise ratio is generally used for quality comparison between the original image and a compressed image. The Peak Signal to Noise Ratio and Mean Square Error are the two error parameters used to measure image compression quality. The MSE shows the growing squared error among the original image and compressed, and PSNR shows a calculation of the peak error. The lesser the value of Mean Square Error will reduce the error. The compression ratio (CR) is the ratio of compressed image compared to uncompressed image size. The bits per pixel (BPP) value will fluctuate for different images and different quality of images.
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Image Compression using Neural Networks & Wavelet Transforms
Editore:
LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202918675
ISBN 13: 9786202918671
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Da: moluna, Greven, Germania
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Image Compression using Neural Networks & Wavelet Transforms
Editore:
LAP LAMBERT Academic Publishing Okt 2020, 2020
ISBN 10: 6202918675
ISBN 13: 9786202918671
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Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Compression provides a means of reducing storage costs and increases the rate of transmission. Image compression reduces the size of graphic images without reducing image quality. Image performance is calculated using certain parameters such as PSNR (peak signal to noise ratio), CR (compression ratio), MSE (mean square error), and (BPP) per pixel bit. Mean Square error is a network performance parameter, it deals the network's Performance according to the mean of squared errors. The Peak signal to noise ratio is generally used for quality comparison between the original image and a compressed image. The Peak Signal to Noise Ratio and Mean Square Error are the two error parameters used to measure image compression quality. The MSE shows the growing squared error among the original image and compressed, and PSNR shows a calculation of the peak error. The lesser the value of Mean Square Error will reduce the error. The compression ratio (CR) is the ratio of compressed image compared to uncompressed image size. The bits per pixel (BPP) value will fluctuate for different images and different quality of images. 80 pp. Englisch. Codice articolo 9786202918671
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Image Compression using Neural Networks & Wavelet Transforms
Editore:
LAP LAMBERT Academic Publishing Okt 2020, 2020
ISBN 10: 6202918675
ISBN 13: 9786202918671
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Neuware -Compression provides a means of reducing storage costs and increases the rate of transmission. Image compression reduces the size of graphic images without reducing image quality. Image performance is calculated using certain parameters such as PSNR (peak signal to noise ratio), CR (compression ratio), MSE (mean square error), and (BPP) per pixel bit. Mean Square error is a network performance parameter, it deals the network's Performance according to the mean of squared errors. The Peak signal to noise ratio is generally used for quality comparison between the original image and a compressed image. The Peak Signal to Noise Ratio and Mean Square Error are the two error parameters used to measure image compression quality. The MSE shows the growing squared error among the original image and compressed, and PSNR shows a calculation of the peak error. The lesser the value of Mean Square Error will reduce the error. The compression ratio (CR) is the ratio of compressed image compared to uncompressed image size. The bits per pixel (BPP) value will fluctuate for different images and different quality of images.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch. Codice articolo 9786202918671
Quantità: 2 disponibili
Immagini fornite dal venditore
Image Compression using Neural Networks & Wavelet Transforms
Editore:
LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202918675
ISBN 13: 9786202918671
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Compression provides a means of reducing storage costs and increases the rate of transmission. Image compression reduces the size of graphic images without reducing image quality. Image performance is calculated using certain parameters such as PSNR (peak signal to noise ratio), CR (compression ratio), MSE (mean square error), and (BPP) per pixel bit. Mean Square error is a network performance parameter, it deals the network's Performance according to the mean of squared errors. The Peak signal to noise ratio is generally used for quality comparison between the original image and a compressed image. The Peak Signal to Noise Ratio and Mean Square Error are the two error parameters used to measure image compression quality. The MSE shows the growing squared error among the original image and compressed, and PSNR shows a calculation of the peak error. The lesser the value of Mean Square Error will reduce the error. The compression ratio (CR) is the ratio of compressed image compared to uncompressed image size. The bits per pixel (BPP) value will fluctuate for different images and different quality of images. Codice articolo 9786202918671
Quantità: 1 disponibili