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http://hdl.handle.net/11375/12744| Title: | L2 Optimized Predictive Image Coding with L∞ Bound |
| Authors: | Chuah, Sceuchin |
| Advisor: | Wu, Xiaolin |
| Department: | Electrical and Computer Engineering |
| Keywords: | L∞-constrained image compression;predictive coding;optimal scalar quantization;Signal Processing;Signal Processing |
| Publication Date: | Apr-2013 |
| Abstract: | <p>In many scientific, medical and defense applications of image/video compression, an <em>l</em><sub>∞ </sub>error bound is required. However, pure <em>l</em><sub>∞</sub>-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, previous <em>l</em><sub>∞</sub>-based image coding methods suffer from poor rate control. In contrast, the <em>l</em><sub>2</sub> error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the <em>l</em><sub>∞</sub> error metric and it offers fine granularity in rate control; but pure <em>l</em><sub>2</sub>-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as <em>l</em><sub>∞</sub>-based methods can. This thesis presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics.</p> |
| URI: | http://hdl.handle.net/11375/12744 |
| Identifier: | opendissertations/7603 8665 3486974 |
| Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| fulltext.pdf | 2.21 MB | Adobe PDF | View/Open |
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