portada Image Compression using Neural Networks & Wavelet Transforms (en Inglés)

Image Compression using Neural Networks & Wavelet Transforms (en Inglés)

Formato

Libro Físico

Autor

Saurabh Jain

Prachi Jain

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x0.5 cm

Peso

0.13 kg.

ISBN13

9786202918671

Categorías

Tecnología de la información: cuestiones generales

Image Compression using Neural Networks & Wavelet Transforms (en Inglés)

Saurabh Jain (Autor) · Prachi Jain (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Image Compression using Neural Networks & Wavelet Transforms (en Inglés)"

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.