Improved Lossless Depth Image Compression
| Autor: | Philipp Dittmann, Gabriel Zachmann, Roland Fischer, Christoph Schröder |
|---|---|
| Přispěvatelé: | Skala, Václav |
| Rok vydání: | 2020 |
| Předmět: |
lossless Compression
0209 industrial biotechnology Computer science Computation Azure Kinect Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology streamování RGB-D RGB-D Streaming 020901 industrial engineering & automation Compression (functional analysis) 0202 electrical engineering electronic engineering information engineering hloubková komprese obrazu bezeztrátová komprese Lossless compression Pixel Depth Image Compression 020207 software engineering Computer Graphics and Computer-Aided Design Computational Mathematics Compression ratio Encoder Algorithm Software Data compression Image compression |
| Zdroj: | Journal of WSCG. 28:168-176 |
| ISSN: | 1213-6972 |
| DOI: | 10.24132/jwscg.2020.28.21 |
| Popis: | Since RGB-D sensors became massively popular and are used in a wide range of applications, depth data compression became an important research topic. Live-streaming of depth data requires quick compression and decompression. Accurate preservation of information is crucial in order to prevent geometric distortions. Custom algorithms are needed considering the unique characteristics of depth images. We propose a real-time, lossless algorithm which can achieve significantly higher compression ratios than RVL. The core elements are an adaptive span-wise intra-image prediction, and parallelization. Additionally, we extend the algorithm by inter-frame difference computation and evaluate the performance regarding different conditions. Lastly, the compression ratio can be further increased by a second encoder, circumventing the lower limit of four-bit per valid pixel of the original RVL algorithm. |
| Databáze: | OpenAIRE |
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