Prediction Theory: The Case of Image Information Preserving Год выпуска: 2012Автор: Saif alZahirИздательство: LAP Lambert Academic PublishingСтраниц: 132ISBN: 9783847347774Описание Data compression is based on the abstraction that data comprises two quantities. The first is the information content and the second is the redundant information. The objective of compression is to remove the redundant information and represent the data by the information content portion only, if possible. As for image signals, for example, the significance of image compression (i.e., coding) is emphasized by the enormous amount of data in raster images. For instance, a typical gray-scale image of 512?512 pixels, with each pixel represented by 8 bits, adds up to 256 kilobytes of data. Hence, removing redundancies from the image is not only highly desired but also imperative for transmission and storage requirements. Linear prediction is a mathematical process, which estimates future values of a discrete – time signal as a linear function of past samples. This book focuses on employing linear prediction theory to image compression for the purpose of information preserving with a...
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AVT Здравствуйте Марина! Хочу Вам сказать большое спасибо за диплом, хоть и пришлось его не много подреставрировать под свою организацию, но в целом всё ОК. Я получил высокие оценки за данную работу после вашего сопровождения. Ещё раз большое спасибо!
