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This overview discusses the motivation, rate control, and wavelets in distributed compression of lightfields, highlighting the gains and challenges in achieving desired quality at low bit rates.
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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.
