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Depth Coding Based on Depth-Texture Motion and Structure Similarities
- Source :
- IEEE Transactions on Circuits and Systems for Video Technology. 25:275-286
- Publication Year :
- 2015
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2015.
-
Abstract
- This paper addresses high performance depth coding in 3D video by making good use of its coded texture video counterpart. The relationship between the depth and its associated texture video in terms of coding mode and motion vector is carefully examined. Our statistical study suggests that the skip-coding mode and its associated motion vectors in the coded texture can be shared for depth coding by saving bit rate at the cost of little increase of distortion, which subsequently results in a nonsequential coding of the depth map. In this sense, coding/prediction of a block can be performed using the skip-coded blocks below and right, which are not available in the conventional sequential coding, thus producing the so-called omnidirectional blocks predicted in the intra-coding by making the best use of (at most) four neighboring blocks. Moreover, in view of the depth-texture structure similarity, a depth-texture cooperative clustering-based prediction method is proposed for cluster-based depth prediction in the intra-coding, which exploits the structure similarity for the current coding block and its neighboring pixels around the block. On the other hand, some large prediction errors may be present for the depth-texture misaligned pixels, which may greatly compromise the coding performance. To deal with these large residuals induced by the depth-texture misalignment, a simple yet effective detection and rectification approach is incorporated in the proposed depth coding scheme. Experimental results show that our proposed depth coding scheme achieves superior rate-distortion performance compared with other relevant coding methods.
- Subjects :
- business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
Coding tree unit
Motion vector
Sub-band coding
Depth map
Media Technology
Computer vision
Artificial intelligence
Electrical and Electronic Engineering
Multiview Video Coding
business
Context-adaptive binary arithmetic coding
Coding (social sciences)
Mathematics
Context-adaptive variable-length coding
Subjects
Details
- ISSN :
- 15582205 and 10518215
- Volume :
- 25
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Circuits and Systems for Video Technology
- Accession number :
- edsair.doi...........e45b43db4c7ebf0de2fdd193ae987093
- Full Text :
- https://doi.org/10.1109/tcsvt.2014.2335471