The last few decades have witnessed what is commonly known as an "information explosion". The advent of the Internet has enabled the sharing of large amounts of information between users in almost every part of the world. This had led to increased bandwidth and storage requirements. These requirements necessitate the development of new techniques to optimize the utilization of existing bandwidth and to minimize storage requirements. In emerging areas of real-time multimedia applications, researchers have successfully developed new approaches, employing techniques such as transform coding, prediction, vector quantization, etc, to efficiently represent and consequently compress data, especially image data.
Recently, multiple transform domain representation techniques have been reported which successfully compress one and multidimensional signals. In this thesis, a novel and efficient codec using multiple transform domain representation in conjunction with split vector quantization is presented, which provides superior coding performance for images. An adaptive scheme that further enhances the representation accuracy of the above codec is also described. Results of simulations of the proposed technique are presented that confirm the improved performance of the codec.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:rtd-1981 |
| Date | 01 January 2003 |
| Creators | Ragothaman, Pradeep |
| Publisher | University of Central Florida |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Retrospective Theses and Dissertations |
Page generated in 0.0025 seconds