A framework for view-dependent hologram representation and adaptive reconstruction

Abstract

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.

A novel high-efficiency holography image compression method, based on HEVC, Wavelet, and nearest-neighbor interpolation

“…They showed that Morlet wavelets can be used effectively for 3DTV display systems better than conventional wavelet methods. Viswanathan et al suggested another framework for view-dependent hologram representation and adaptive reconstruction [11]. There, some wavelet coefficients are eliminated according to the user's position.…”

A Hierarchical modified AV1 codec for compression cartesian form of holograms in holo and object planes

“…The obtained results were not compared to wavelet-based methods, but compression parameters and their effect on the quality and run time of some types of holograms were investigated. Viswanathan et al [14] dealt with wavelet compression and proposed an adaptive model to improve quality and optimize structure in decoding step. It explores the Morlet wavelet in addition to Gabor wavelet.…”

Wave Atoms for Lossy Compression of Digital Holograms

“…Leaving the design of the image coding techniques unaltered, i.e., adhering to the ∼ 1/f 2 decay of spectral amplitude with spatial frequency f , will fail on the considered holograms, which possess an almost homogeneous spectral amplitude distribution. Improvements on the compression efficiency could be achieved either by generalization of the wavelet transforms [7,8] or by devising completely different designs such as [9,10]. The latter ones consider a viewing perspective as given and encode only the relevant information from the 4D space-frequency domain, using Gabor wavelets.…”