Award Date

1-1-1995

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Number of Pages

162

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.

Keywords

Adaptive; Compression; Encoding; Image; Level; Methods; Multi; Statistical; Transforms

Controlled Subject

Computer science

File Format

pdf

File Size

4874.24 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/hbov-c529


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