Sturgill, David Brian.Van Ruitenbeek, Benjamin D.Baylor University. Dept. of Computer Science.2009-08-252009-08-252009-082009-08-25http://hdl.handle.net/2104/5397Includes bibliographical references (p. 71-73).We present a novel method for sparse signal recovery using Particle Swarm Optimization and demonstrate an application in image compression. Images are compressed with compressive sampling, and then reconstructed with particle swarm techniques. Several enhancements to the basic particle swarm algorithm are shown to improve signal recovery accuracy. We also present techniques specifically for reconstructing sparse image data and evaluate their performance.vii, 73 p. : ill.702104 bytes511205 bytesapplication/pdfapplication/pdfen-USBaylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission.Image compression.Mathematical optimization -- Computer programs.Swarm intelligence.ThesisWorldwide access