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Technical Program
Paper Detail
| Paper: | TA-P8.5 |
| Session: | Wavelets and Filter Banks |
| Time: | Tuesday, October 10, 09:40 - 12:20 |
| Presentation: |
Poster
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| Title: |
LOW-RATE REDUCED COMPLEXITY IMAGE COMPRESSION USING DIRECTIONLETS |
| Authors: |
Vladan Velisavljevic; Deutsche Telekom Laboratories | | | | | Baltasar Beferull-Lozano; Universidad de Valencia | | | | | Martin Vetterli; Ecole Polytechnique Fédérale de Lausanne (EPFL) | | | | | Pier Luigi Dragotti; Imperial College London | | |
| Abstract: |
The standard separable two-dimensional wavelet transform has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the complexity of the standard two-dimensional wavelet transform and substantially lower than the complexity of other similar approaches. We also present a zerotree-based image compression algorithm using directionlets that strongly outperforms the corresponding method based on the standard wavelets at low bit rates. |
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