An Evolutionary Approach to Image Compression in the Discrete Cosine Transform Domain
Abstract (Summary)
An Evolutionary Approach to Image Compression in the
Discrete Cosine Transform Domain
by
Benjamin E. Banham, Master of Science
Utah State University, 2008
Major Professor: Dr. Xiaojun Qi
Department: Computer Science
This paper examines the application of genetic programming to image
compression while working in the frequency domain. Several methods utilized by JPEG
encoding are applied to the image before utilizing a genetic programming system.
Specifically, the discrete cosine transform (DCT) is applied to the original image,
followed by the zig-zag scanning of DCT coefficients. The genetic programming system
is finally applied to the one-dimensional array resulting from the zig-zag scan. The
research takes an existing genetic programming system developed for the spatial domain
and develops DCT domain functionality. The results from the DCT domain-based
genetic programming system are compared with those from the spatial domain-based
system, and show improvements to the image quality with a reduction up to half of the
evolved image’s average error. The results show that working in the frequency domain
has advantages over the spatial domain. Several methods to exploit these advantages are
proposed and evaluated. (55 pages)
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Bibliographical Information:
Advisor:
School:Utah State University
School Location:USA - Utah
Source Type:Master's Thesis
Keywords:
ISBN:
Date of Publication:12/01/2008