KEYWORDS: Holograms, Holography, Transform theory, Signal to noise ratio, Reconstruction algorithms, Fourier transforms, Visualization, Digital holography, Video compression, 3D video compression
Holography is often considered as the most promising 3D visualization technique, creating virtual images indistinguishable from the real ones. However, one the main barrier to the adoption of holographic displays in wide 3D viewing systems is the very large amount of information contained in a hologram. Indeed, a hologram with a large size and wide viewing angle contains terabytes of data, urging the need for holographic data coding algorithms. In this paper, we propose a data coding algorithm suitable to the compression of holograms containing several billions of pixels. In our proposed approach, each holographic frame is subdivided into pixel blocks which are 2D Fourier transformed. The pixels thus obtained are rearranged to form new complex-valued segments whose amplitudes have characteristics close to orthographic projection images. These segments are ordered in sequence and their real and imaginary parts are encoded using the High-Efficiency Video Coding (HEVC) Main 4:4:4 coding profile with 4:0:0 chroma sampling.
Due to its ability to reproduce the correct focus cues, holography is considered as a promising display technology for Augmented Reality glasses. However, since it contains a large amount of data, the calculation of a hologram is a time-demanding process, resulting in prohibiting head-motion-to-photon latency. In this paper, we propose a real-time hologram calculation method based on two modules: an offline pre-computation module and an on-the-fly hologram synthesis module. In the offline calculation module, the omnidirectional light field scattered by each scene object is individually pre-computed and stored in a Look-Up Table (LUT). Then, in the hologram synthesis module, the light waves corresponding to the viewer’s position and orientation are extracted from the LUT in real-time to compute the hologram. Contrarily to previously proposed methods, our approach handles several independent scene objects and arbitrary user positions and orientations. Experimental results show that the proposed method is able to compute full-HD holograms at more than 256 frames per second, enabling its use in Augmented Reality applications.
Digital holography is an emerging technology for 3D visualization which is expected to dethrone conventional stereoscopic devices in the future. Aside from their specific signal properties, high quality holograms with broad viewing angles contain massive amount of data. For a reasonable transmission time, efficient scalable compression schemes are needed to bridge the gap between the overwhelming volume of data and the limited bandwidth of the communication channels. The viewpoint scalability is a powerful property since it allows to encode and transmit only the information corresponding to the observer’s view. However, this approach imposes an online encoding at the server which may increase the latency of the transmission chain. To overcome this hurdle, we propose a scalable compression framework based on Gabor-wavelets decomposition, where the whole hologram is encoded offline. First, the observer plane is divided into spatial blocks. Then, the Gabor atoms are assigned to these blocks by exploiting the duality between Gabor wavelets and light rays. The atoms of each block are then classified into different layers according to their importance for the reconstruction and encoded in packets. At the decoder side, the atoms’ packets are progressively decoded based on the viewer’s position. Then, the corresponding sub-hologram is generated using a GPU implementation. Results show that our approach enables a practical progressive streaming of digital holograms with a low latency.
In this paper we investigate the suitability of Gabor Wavelets for an adaptive partial reconstruction of holograms based on the viewer position. Matching Pursuit is used for a sparse light rays decomposition of holographic patterns. At the decoding stage, sub-holograms are generated by selecting the diffracted rays corresponding to a specific area of visualization. The use of sub-holograms has been suggested in the literature as an alternative to full compression, by degrading a hologram with respect to the directional degrees of freedom. We present our approach in a complete framework for color digital holograms compression and explain, in details, how it can be efficiently exploited in the context of holographic Head-Mounted Displays. Among other aspects, encoding, adaptive reconstruction and selective degradation are studied.
The hybrid point-source/wave-field method is a newly proposed approach for Computer-Generated Hologram (CGH) calculation, based on the slicing of the scene into several depth layers parallel to the hologram plane. The complex wave scattered by each depth layer is then computed using either a wave-field or a point-source approach according to a threshold criterion on the number of points within the layer. Finally, the complex waves scattered by all the depth layers are summed up in order to obtain the final CGH. Although outperforming both point-source and wave-field methods without producing any visible artifact, this approach has not yet been used for animated holograms, and the possible exploitation of temporal redundancies has not been studied. In this paper, we propose a fast computation of video holograms by taking into account those redundancies. Our algorithm consists of three steps. First, intensity and depth data of the current 3D video frame are extracted and compared with those of the previous frame in order to remove temporally redundant data. Then the CGH pattern for this compressed frame is generated using the hybrid point-source/wave-field approach. The resulting CGH pattern is finally transmitted to the video output and stored in the previous frame buffer. Experimental results reveal that our proposed method is able to produce video holograms at interactive rates without producing any visible artifact.
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 view- dependent representation along with Morlet wavelets form a good starting step for compressing holographic data for next generation 3DTV applications.
An 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 viewpointbased 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.
In this paper we propose a new method based on Second Generation Wavelets (SGW), a recently emerged mathematic transform, already successfully applied in 3d coding. This new wavelet transform (SGW) applied to meshes is performed using the powerful lifting scheme, keeping the main features of the first generation wavelets whilst introducing some useful properties such as: analysis on general domains (typically arbitrary, non linear domains of Rn), adapted basis for weighted approximation/interpolation and weighted measure and transform adapted to irregular sampled data. Thus in this paper we propose a video coder based on second generation wavelet theory and mesh geometry. In fact, we focus on video coder error images which are mainly composed of high frequencies and singularities, i.e. typically the kind of data that second generation wavelet can successfully process. The main advantage is that these wavelets can be designed to fit exactly on singularities, shapes, textures, and edges. Hence, we can further reduce redundancy and improve coding efficiency over those peculiar settings.
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