Holographic Sensing (original) (raw)
Related papers
2020
Holographic representations of data enable distributed storage with progressive refinement when the stored packets of data are made available in any arbitrary order. In this paper, we propose and test patch-based transform coding holographic sensing of image data. Our proposal is optimized for progressive recovery under random order of retrieval of the stored data. The coding of the image patches relies on the design of distributed projections ensuring best image recovery, in terms of the ell_2\ell_2ell_2 norm, at each retrieval stage. The performance depends only on the number of data packets that has been retrieved thus far. Several possible options to enhance the quality of the recovery while changing the size and number of data packets are discussed and tested. This leads us to examine several interesting bit-allocation and rate-distortion trade offs, highlighted for a set of natural images with ensemble estimated statistical properties.
Holographic representations of images
IEEE Transactions on Image Processing, 1998
We discuss a new type of holographic image representations that have advantages in a "distributed" world. We call these representations holographic. Arbitrary portions of a holographic representation enable reconstruction of the whole image, with distortions that decrease gradually with the increase in the size of the portions available. Holographic representations enable progressive refinement in image communication or retrieval tasks, with no restrictions on the order in which the data fragments (sections of the representation) are accessed or become available. Index Terms-Holographic representations, progressive refinement, pseudorandom uniform samplings, random phase Fourier transforms. Alfred M. Bruckstein received the B.Sc. and M.Sc. degrees in electrical engineering from the Technion-Israel Institute of Technology, Haifa, in 1977 and 1980, respectively, and the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, in 1984. Since October 1984, he has been with the Technion, where he is Professor of Computer Science. He is a frequent visitor to Bell Laboratories, Murray Hill, NJ. His present research interests include image analysis, image processing pattern recognition, ants, robotics, and computer graphics. He also has done work in estimation theory, signal processing, algorithmic aspects of inverse scattering, point processes and mathematical models in neurophysiology. Prof. Bruckstein is a member of SIAM, MAA, and AMS.
Patch-Based Holographic Image Sensing
2021
Holographic representations of data enable distributed storage with progressive refinement when the stored packets of data are made available in any arbitrary order. In this paper, we propose and test patch-based transform coding holographic sensing of image data. Our proposal is optimized for progressive recovery under random order of retrieval of the stored data. The coding of the image patches relies on the design of distributed projections ensuring best image recovery, in terms of the `2 norm, at each retrieval stage. The performance depends only on the number of data packets that have been retrieved thus far. Several possible options to enhance the quality of the recovery while changing the size and number of data packets are discussed and tested. This leads us to examine several interesting bit-allocation and rate-distortion trade-offs, highlighted for a set of natural images with ensemble estimated statistical properties.
Holographic-type communication: A new challenge for the next decade
ITU Journal on Future and Evolving Technologies
Holographic-Type Communication (HTC) is an important technology that will be supported by 6G and beyond wireless systems. It provides truly immersive experiences for a large number of novel applications, such as holographic telepresence, healthcare, retail, education, training, entertainment, sports, and gaming, by displaying multi-view high resolution 3D holograms of humans or objects/items and creating multi-sensory media (mulsemedia), including audio, haptic, smell, and taste. HTC faces great challenges in transmitting high volume data with guaranteed end-to-end latency which cannot be addressed by existing communication and networking technologies. The contribution of this paper is two-fold. First, it introduces the basics and generic architectures of HTC systems. The encoding and decoding of hologram and mulsemedia are discussed, and the envisioned use cases and technical requirements are introduced. Second, this paper identifies limitations of existing wireless and wired netwo...
Applied Optics, 1968
Very large bandwidths are required for the transmission of holographic data for systems such as TV. This paper presents a technique in which the large bandwidths normally required are traded off for either increased noise or decreased resolution in the image. The light radiated from the object is diffracted by an intermediate dispersion medium and collected at the hologram aperture. Correct illumination of this hologram provides an image beam that passes back through the intermediate medium and comes to focus in the space originally occupied by the object. By proper selection of the dispersion medium, the hologram aperture can be made extremely small, thus representing a large data reduction. The three dimensionality of the image and the original viewing angles are maintained. Included in the paper are experimental results that show reconstructed images after a data reduction of as much as 3600.
Holographic Screens Are Classical Information Channels
Quantum Reports, 2020
The ideas of classical communication and holographic encoding arise in different parts of physics. Here, we show that they are equivalent. This allows for us to reformulate the holographic principle independently of spacetime, as the principle that holographic screens encode interaction eigenvalues.
Modulation codingfor pixel-matched holographic data storage
Optics Letters, 1997
We describe a digital holographic storage system for the study of noise sources and the evaluation of modulation and error-correction codes. A precision zoom lens and Fourier transform optics provide pixel-to-pixel matching between any input spatial light modulator and output CCD array over magnif ications from 0.8 to 3. Holograms are angle multiplexed in LiNbO 3 :Fe by use of the 90 ± geometry, and reconstructions are detected with a 60-frame͞s CCD camera. Modulation codes developed on this platform permit image transmission down to signal levels of ϳ2000 photons per ON camera pixel, at raw bit-error rates (BER's) of better than 10 25 . Using an 8 -12-pixel modulation code, we have stored and retrieved 1200 holograms (each with 45,600 user bits) without error, for a raw BER of ,2 3 10 28 .
Coding tradeoffs for high-density holographic data storage
1999
We present an initial experimental evaluation of coding and signal processing tradeoffs in high-density holographic data storage. Block-based and low-pass modulation codes, predistortion of holographic pages during recording (pre- processing), and conventional equalization (post-processing) are compared using a few recorded holograms. The relative gain in number of stored holograms is obtained by measuring BER as a function of readout power:
Dynamically structured holographic memory : a hybrid of discrete and distributed representation
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Nonlinear equalization for holographic data storage systems
Applied Optics, 2006
Despite the fact that the channel in a holographic data-storage system is nonlinear, most of the existing approaches use linear equalization for data recovery. We present a novel and simple to implement nonlinear equalization approach based on a minimum mean-square-error criterion. We use a quadratic equalizer whose complexity is comparable to that of a linear equalizer. We also explore the effectiveness of a nonlinear equalization target as compared with the conventional linear target. Bit-error-rate (BER) performance is studied for channels having electronics noise, optical noise, and a different span of intersymbol interference. With a linear target, whereas the linear equalizer exhibits an error floor in the BER performance, the quadratic equalizer significantly improves the performance with no sign of error floor even up to 10 Ϫ7. With a nonlinear target, whereas the quadratic equalizer provides an additional performance gain of 1-2 dB, the error-floor problem of the linear equalizer has been considerably alleviated, thereby significantly improving the latter's performance. A theoretical performance analysis of the nonlinear receiver with non-Gaussian noise is also presented. A simplified approach is developed to compute the underlying probability density functions, optimum detector threshold, and BER using the theoretical analysis. Numerical results show that the theoretical predictions agree well with simulations.