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1.
Appl Opt ; 52(1): A254-68, 2013 Jan 01.
Article in English | MEDLINE | ID: mdl-23292401

ABSTRACT

This paper discusses processing techniques for an adaptive digital holographic video service in various reconstruction environments, and proposes two new scalable coding schemes. The proposed schemes are constructed according to the hologram generation or acquisition schemes: hologram-based resolution-scalable coding (HRS) and light source-based signal-to-noise ratio scalable coding (LSS). HRS is applied for holograms that are already acquired or generated, while LSS is applied to the light sources before generating digital holograms. In the LSS scheme, the light source information is lossless coded because it is too important to lose, while the HRS scheme adopts a lossy coding method. In an experiment, we provide eight stages of an HRS scheme whose data compression ratios range from 1:1 to 100:1 for each layered data. For LSS, four layers and 16 layers of scalable coding schemes are provided. We experimentally show that the proposed techniques make it possible to service a digital hologram video adaptively to the various displays with different resolutions, computation capabilities of the receiver side, or bandwidths of the network.

2.
Appl Opt ; 51(18): 4003-12, 2012 Jun 20.
Article in English | MEDLINE | ID: mdl-22722274

ABSTRACT

In this paper we propose a hardware architecture for high-speed computer-generated hologram generation that significantly reduces the number of memory access times to avoid the bottleneck in the memory access operation. For this, we use three main schemes. The first is pixel-by-pixel calculation, rather than light source-by-source calculation. The second is a parallel calculation scheme extracted by modifying the previous recursive calculation scheme. The last scheme is a fully pipelined calculation scheme and exactly structured timing scheduling, achieved by adjusting the hardware. The proposed hardware is structured to calculate a row of a computer-generated hologram in parallel and each hologram pixel in a row is calculated independently. It consists of and input interface, an initial parameter calculator, hologram pixel calculators, a line buffer, and a memory controller. The implemented hardware to calculate a row of a 1920×1080 computer-generated hologram in parallel uses 168,960 lookup tables, 153,944 registers, and 19,212 digital signal processing blocks in an Altera field programmable gate array environment. It can stably operate at 198 MHz. Because of three schemes, external memory bandwidth is reduced to approximately 1/20,000 of the previous ones at the same calculation speed.

3.
Opt Express ; 19(9): 8750-61, 2011 Apr 25.
Article in English | MEDLINE | ID: mdl-21643127

ABSTRACT

This paper proposes a new hardware architecture to speed-up the digital hologram calculation by parallel computation. To realize it, we modify the computer-generated hologram (CGH) equation and propose a cell-based very large scale integrated circuit architecture. We induce a new equation to calculate the horizontal or vertical hologram pixel values in parallel, after finding the calculation regularity in the horizontal or vertical direction from the basic CGH equation. We also propose the architecture of the computer-generated hologram cell consisting of an initial parameter calculator and update-phase calculators based on the equation, and then implement them in hardware. Modifying the equation could simplify the hardware, and approximating the cosine function could optimize the hardware. In addition, we show the hardware architecture to parallelize the calculation in the horizontal direction by extending computer-generated holograms. In the experiments, we analyze hardware resource usage and the performance-capability characteristics of the look-up table used in the computer-generated hologram cell. These analyses make it possible to select the amount of hardware to the precision of the results. Here, we used the platform from our previous work for the computer-generated hologram kernel and the structure of the processor.


Subject(s)
Algorithms , Holography/instrumentation , Image Enhancement/instrumentation , Imaging, Three-Dimensional/instrumentation , Signal Processing, Computer-Assisted/instrumentation , Equipment Design , Equipment Failure Analysis
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