This thesis explores the possibilities of avoiding the issues generally associated with compression of noisy imagery, through the usage of vector quantization. By utilizing the learning aspects of vector quantization, image processing operations such as noise reduction could be implemented in a straightforward way. Several techniques are presented and evaluated. A direct comparison shows that for noisy imagery, vector quantization, in spite of it's simplicity, has clear advantages over MPEG-4 encoding.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-2377 |
| Date | January 2004 |
| Creators | Cronvall, Per |
| Publisher | Linköpings universitet, Institutionen för systemteknik, Institutionen för systemteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | LiTH-ISY-Ex, ; 3541 |
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