Image Data Compression
| dc.citation.bibtexName | mastersthesis | en_US |
| dc.citation.journalTitle | Masters Thesis | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.creator | Wei, Dong | en_US |
| dc.date.accessioned | 2007-10-31T01:09:31Z | en_US |
| dc.date.available | 2007-10-31T01:09:31Z | en_US |
| dc.date.issued | 1995-05-01 | en_US |
| dc.date.modified | 2005-05-08 | en_US |
| dc.date.submitted | 2001-08-22 | en_US |
| dc.description | Masters Thesis | en_US |
| dc.description.abstract | Wavelet-based multi-resolution representation has become a cutting-edge technology in the area of image data compression. Though the discrete wavelet transform is closely related to the perfect-reconstruction octave-band filter banks used in subband coding schemes, wavelets have provided very promising new ideas and insights for image data compression. Wavelet-based coding techniques have achieved competitive performance compared with other well-known image coding techniques. This thesis develops a general framweork for wavelet-based lossy image coding. We discuss two application problems and develop the corresponding fast algorithms using wavelet-based techniques (e.g., optimum wavelet-packet bases selection, wavelet-domain soft-thresholding). | en_US |
| dc.identifier.citation | "Image Data Compression," <i>Masters Thesis,</i> 1995. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/20442 | en_US |
| dc.language.iso | eng | en_US |
| dc.subject | wavelet | en_US |
| dc.subject | image data compression | en_US |
| dc.subject.keyword | wavelet | en_US |
| dc.subject.keyword | image data compression | en_US |
| dc.subject.other | Image Processing and Pattern analysis | en_US |
| dc.title | Image Data Compression | en_US |
| dc.type | Thesis | en_US |
| dc.type.dcmi | Text | en_US |
| thesis.degree.level | Masters | en_US |
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