Lossless depth map coding using binary tree based decomposition and context-based arithmetic coding
- Authors: Shahriyar, Shampa , Murshed, Manzur , Ali, Mortuza , Paul, Manoranjan
- Date: 2016
- Type: Text , Conference proceedings , Conference paper
- Relation: 2016 IEEE International Conference on Multimedia and Expo, ICME 2016; Seattle, United States; 11th-15th July 2016; published in Proceedings of the 2016 IEEE International Conference on Mulitmedia and Expo Vol. 2016-August, p. 1-6
- Full Text: false
- Reviewed:
- Description: Depth maps are becoming increasingly important in the context of emerging video coding and processing applications. Depth images represent the scene surface and are characterized by areas of smoothly varying grey levels separated by sharp edges at the position of object boundaries. To enable high quality view rendering at the receiver side, preservation of these characteristics is important. Lossless coding enables avoiding rendering artifacts in synthesized views due to depth compression artifacts. In this paper, we propose a binary tree based lossless depth coding scheme that arranges the residual frame into integer or binary residual bitmap. High spatial correlation in depth residual frame is exploited by creating large homogeneous blocks of adaptive size, which are then coded as a unit using context based arithmetic coding. On the standard 3D video sequences, the proposed lossless depth coding has achieved compression ratio in the range of 20 to 80. © 2016 IEEE.
- Description: Proceedings - IEEE International Conference on Multimedia and Expo
A novel depth motion vector coding exploiting spatial and inter-component clustering tendency
- Authors: Shahriyar, Shampa , Murshed, Manzur , Ali, Mortuza , Paul, Manoranjan
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: Visual Communications and Image Processing, VCIP 2015; Singapore; 13th-16th December 2015 p. 1-4
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text: false
- Reviewed:
- Description: Motion vectors of depth-maps in multiview and free-viewpoint videos exhibit strong spatial as well as inter-component clustering tendency. This paper presents a novel coding technique that first compresses the multidimensional bitmaps of macroblock mode and then encodes only the non-zero components of motion vectors. The bitmaps are partitioned into disjoint cuboids using binary tree based decomposition so that the 0's and 1's are either highly polarized or further sub-partitioning is unlikely to achieve any compression. Each cuboid is entropy-coded as a unit using binary arithmetic coding. This technique is capable of exploiting the spatial and inter-component correlations efficiently without the restriction of scanning the bitmap in any specific linear order as needed by run-length coding. As encoding of non-zero component values no longer requires denoting the zero value, further compression efficiency is achieved. Experimental results on standard multiview test video sequences have comprehensively demonstrated the superiority of the proposed technique, achieving overall coding gain against the state-of-the-art in the range [22%, 54%] and on average 38%. © 2015 IEEE.
- Description: 2015 Visual Communications and Image Processing, VCIP 2015