Name
Abstract | ||
|---|---|---|
We consider a variable block size compressed sensing (CS) framework for high efficiency depth map coding. In this context, quad-tree decomposition is performed on a depth image to differentiate irregular uniform and edge areas prior to CS acquisition. To exploit temporal correlation and enhance coding efficiency, such quad-tree based CS acquisition is further extended to inter-frame encoding, where block partitioning is performed independently on the I frame and each of the subsequent residual frames. At the decoder, pixel domain total-variation minimization is performed for high quality depth map reconstruction. Experiments presented herein illustrate and support these developments. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6853721 | ICASSP |
Keywords | Field | DocType |
depth map,decoder,sparse signals,image coding,codecs,quad-tree partitioned compressed sensing,inter-frame encoding,quad-tree decomposition,high quality depth map reconstruction,sub-nyquist sampling,image reconstruction,compressed sensing,depth map coding,pixel domain total-variation minimization,total-variation,depth image,decoding,total variation,encoding,minimization,sensors | Block size,Residual,Algorithmic efficiency,Pattern recognition,Computer science,Artificial intelligence,Pixel,Depth map,Compressed sensing,Encoding (memory),Quadtree | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Liu | 1 | 60 | 5.05 |
| Krishna Rao Vijayanagar | 2 | 13 | 3.38 |
| Joohee Kim | 3 | 12 | 2.71 |