Abstract
An efficient algorithm to compress high dynamic range (HDR) videos into layered bitstreams is proposed in this work. First, we separate an HDR video sequence into a tone-mapped low dynamic range (LDR) sequence and a ratio sequence, which represents ratios between HDR and LDR pixel values. Then, we encode the LDR and ratio sequences to maximize the rate-distortion (R-D) performance by extending the standard H.264/AVC codec. Specifically, we estimate the distortion of the HDR sequence from those of the LDR sequence and the ratio sequence, and then allocate a limited bit budget to the LDR sequence and the ratio sequence efficiently to maximize the qualities of both LDR and HDR sequences. Conventional LDR devices use only the LDR stream, whereas HDR devices reconstruct the HDR video from the LDR and ratio streams. Simulation results show that the proposed algorithm provides significantly better R-D performance than conventional HDR video coding techniques.
Original language | English |
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Pages (from-to) | 908-923 |
Number of pages | 16 |
Journal | Journal of Visual Communication and Image Representation |
Volume | 23 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2012 Aug |
Bibliographical note
Funding Information:We thank Dr. Grzegorz Krawczyk for making the HDR sequences “Tunnel” and “Sun” available for our experiments and Dr. Rafał Mantiuk for providing us valuable comments and their experimental data on the “Tunnel” sequence for comparison. This work was supported partly by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2012-011031 ), and partly by the Global Frontier R&D Program on Human-centered Interaction for Coexistence, funded by the National Research Foundation of Korea grant funded by the Korean Government (MEST) ( NRF-M1AXA003-2011-0031648 ).
Keywords
- Backward compatibility
- H.264/AVC
- High dynamic range video
- Human visual system
- Layered coding
- Rate-distortion optimization
- Tone mapping
- Video coding
ASJC Scopus subject areas
- Signal Processing
- Media Technology
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering