Subband coding of images using trellis coded quantization
| dc.contributor.advisor | Marcellin, Michael W. | en_US |
| dc.contributor.author | VonColln, Eric, 1967- | |
| dc.creator | VonColln, Eric, 1967- | en_US |
| dc.date.accessioned | 2013-04-03T13:09:55Z | |
| dc.date.available | 2013-04-03T13:09:55Z | |
| dc.date.issued | 1991 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/278018 | |
| dc.description.abstract | An image coding scheme combining subband coding and the established energy compaction technique of the discrete cosine transform (DCT) with trellis coded quantization (TCQ) is introduced. Image spectrums are split into 16 subband images using a quadrature mirror filter bank, and the DCT is performed on the lowest subband. The data is quantized using TCQ, transmitted and recombined at the receiver. It is shown that quantizing the subband data with TCQ decreases the mean-squared error (MSE) incurred in the quantization step, versus that of a Lloyd-Max scalar quantizer. | |
| dc.language.iso | en_US | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.subject | Engineering, Electronics and Electrical. | en_US |
| dc.title | Subband coding of images using trellis coded quantization | en_US |
| dc.type | text | en_US |
| dc.type | Thesis-Reproduction (electronic) | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | masters | en_US |
| dc.identifier.proquest | 1346440 | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.name | M.S. | en_US |
| dc.identifier.bibrecord | .b27227741 | en_US |
| refterms.dateFOA | 2018-05-29T08:27:24Z | |
| html.description.abstract | An image coding scheme combining subband coding and the established energy compaction technique of the discrete cosine transform (DCT) with trellis coded quantization (TCQ) is introduced. Image spectrums are split into 16 subband images using a quadrature mirror filter bank, and the DCT is performed on the lowest subband. The data is quantized using TCQ, transmitted and recombined at the receiver. It is shown that quantizing the subband data with TCQ decreases the mean-squared error (MSE) incurred in the quantization step, versus that of a Lloyd-Max scalar quantizer. |
