Name
Abstract | ||
|---|---|---|
In video coding, in-loop filtering has attracted attention due to its increasing coding performances. In this paper the shearlet-based loop filter is proposed using a sparsifying transform, the shearlet transform, which can identify the important structures of natural images such as edges in the sparse transform domain. This allows for separating efficiently the important information from noise components. Our novel approach for in-loop filtering is to apply a shearlet transform to the decoded image, separating important structures from noise and perform an inverse shearlet transform combined with Wiener filtering. This effectively removes compression artefacts due to quantization noise and keeps the important features of the original image. Simulation results show that our shearlet based loop filter can improve the state-of-the-art video coding standard HEVC through up to 10.5% bit rate reduction along with improved subjective visual quality. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.23919/EUSIPCO.2018.8553579 | European Signal Processing Conference |
Keywords | DocType | ISSN |
shearlets,sparsity,in-loop filtering,Wiener filtering,classification | Conference | 2076-1465 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Johannes Erfurt | 1 | 0 | 0.34 |
| Wang-Q Lim | 2 | 195 | 9.41 |
| Heiko Schwarz | 3 | 815 | 120.48 |
| Detlev Marpe | 4 | 869 | 143.26 |
| Thomas Wiegand | 5 | 3348 | 279.51 |