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Distributed Compression of Lightfields. Sumanth Jagannathan and Primoz Skraba. Overview. Motivation Distributed Compression of Lightfields Rate Control Wavelets Conclusion. Lightfields. Lightfield data of one object from many views Large amount of correlated data
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Distributed Compression of Lightfields Sumanth Jagannathan and Primoz Skraba
Overview • Motivation • Distributed Compression of Lightfields • Rate Control • Wavelets • Conclusion
Lightfields • Lightfield data of one object from many views • Large amount of correlated data • Distributed compression • Lower bandwidth requirement • Lower image sensor complexity • Wyner-Ziv coding • Thought of as a Slepian-Wolf coder followed by a quantizer • Done in practice with turbo coder • Use Key views to generate side information at the decoder • Assume that we have perfect geometry information
Rate Control • Problem definition • Obtain desired quality given the total rate of key views and Wyner-Ziv views • Many degrees of freedom • Our approach • Fix quality of key views • Choose quantization step size of W-Z views • Implementation • Effect of bit rate on side information quality
Wavelet decomposition simulations result • High Wyner-Ziv rates – even in low sub-bands • Problem with turbo encoder/decoder – outliers? • Entropy calculations show some performance gains of DWT based Wyner-Ziv coders over pixel domain coders Wavelet Transform Coder • Wyner-Ziv coding in the transform domain • Low frequency sub-bands should be well correlated, resulting in low Wyner-Ziv rates • Higher frequency sub-bands are quantized with lower resolution (compression gain)
Conclusion • Gains at low bit rates using Wyner-Ziv coding • For rate control • Quality of key views determines Wyner-Ziv quantization step size • Number of key views is very important • Optimal number of key frames exists which will maximize PSNR for a total given rate • For Wavelets • Simulations give poor performance • Entropy based calculations indicate some gains • Simulation model and turbo encoder/decoder needs to be re-examined
Acknowledgements We would like to thank Prof. Girod, Xiaoqing, Anne, David, Prashant, and Shantanu for their helpful discussions.
