International audienceAn analysis and discussion on the relevance of various wavelet schemes for hologram compression and reconstruction when the rendering configuration makes it possible to exploit selective refinements to perform a viewpoint-based degraded reconstruction. It is observed that Gabor wavelet bases have better time-frequency localization as compared to Fresnelet bases and hence are well suited for view-dependent compression techniques for hologram reconstruction

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We provide an efficient method of using Morlet wavelets for transforming a hologram and reconstructing parts of a scene based on the position of viewer by using a sparse set of Morlet transformed coefficients. We provide a design of a Morlet wavelet and explain an efficient discretization method for the application of view-dependent representation systems. Results are provided based on the numerical reconstruction, and it is shown that viewdependent representation along with Morlet wavelets form a good starting step for compressing holographic data for next generation 3DTV applications.

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In this paper, we present a complete framework for networked hologram adaptive transmission; we propose a well-suited wavelet basis allowing efficient local diffractive pattern extraction according to the user position, expose the relations between observer parameters and the pruning in the wavelet decomposition representation, and explain how the reconstruction is performed. The proposed framework has been validated on an experimental setup involving a kinect sensor for viewer position estimation.