Date of Award:
12-2008
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Computer Science
Committee Chair(s)
Xiaojun Qi
Committee
Xiaojun Qi
Committee
Stephen J. Allan
Committee
Daniel W. Watson
Abstract
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.
Checksum
41e27fba3b9579236fe66b5fbdb49298
Recommended Citation
Banham, Benjamin E., "An Evolutionary Approach to Image Compression in the Discrete Cosine Transform Domain" (2008). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 5.
https://digitalcommons.usu.edu/etd/5
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