New methods in image compression using multi-level transforms and adaptive statistical encoDing
type: CreativeWork
description: The need to meet the demand for high quality digital images, with comparatively modest storage requirements, is driving the development of new image compression techniques. This demand has spurred new techniques based on time to frequency spatial transformation methods. At the core of these methods are a family of transformations built on basis sets called "wavelets." The wavelet transform permits an image to be represented in a substantially reduced space by transferring the energy of the image to a smaller set of coefficients. Although these techniques are lossy as the compression ratio rises, very adequate reconstructions can be made from surprisingly small sets of coefficients. This work explores the transformation process, storage of the representation and the application of these techniques to 24-bit color images. A working color image compression model is illustrated.
abstract: The need to meet the demand for high quality digital images, with comparatively modest storage requirements, is driving the development of new image compression techniques. This demand has spurred new techniques based on time to frequency spatial transformation methods. At the core of these methods are a family of transformations built on basis sets called "wavelets." The wavelet transform permits an image to be represented in a substantially reduced space by transferring the energy of the image to a smaller set of coefficients. Although these techniques are lossy as the compression ratio rises, very adequate reconstructions can be made from surprisingly small sets of coefficients. This work explores the transformation process, storage of the representation and the application of these techniques to 24-bit color images. A working color image compression model is illustrated.
author: Pike, Thomas William
language: English
date published: 1995-01-01T08:00:00Z
date modified: 2026-07-24T05:24:31Z
provider: University of Nevada - Las Vegas
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Nevada, Las Vegas

PropertyValue
property ID: DOI
value: 10.25669/hbov-c529