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Variable block-size compressed sensing for depth map coding
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DOI：10.1007/s11042-019-7545-0.png)
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Compressed sensing (CS) is the theory and practice of sub-Nyquist sampling of sparse signals of interest. Perfect reconstruction is possible with much fewer than the Nyquist required number of data samples. In this work, we consider a variable block-size CS architecture for fast compression of depth maps for three-dimensional video (3DV) applications. While existing CS-based depth map coding methods encode depth maps with equal block size, the proposed algorithm partitions a depth map into smooth and edge blocks of variable sizes via rate-distortion optimized quad-tree decomposition. CS is then performed on edge blocks, and eight-bit encoding is performed on smooth blocks. At the decoder, high quality depth map reconstruction is achieved by minimizing the spatial total-variation. Experimental results show that at a small extra expense of encoder complexity, the proposed variable block-size compressed sensing has enhanced significantly the rate-distortion performance over existing low-complexity CS-based depth map coding algorithms.
Keyword:
Compressed sensing
Depth map
Quad-tree decomposition
Rate-distortion optimization
Three-dimensional video
Total-variation
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3
论文数:
2.0W
被引数:
3.2W
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