An efficient implementation of a phase unwrapping kernel on reconfigurable hardware

Braganza, S.; Leeser, Miriam

doi:10.1109/asap.2008.4580168

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…However, this algorithm requires time on the order of minutes to unwrap a single 640 x 480 image of quantitative phase on a computer using a 1.8 GHz processor and 1.5 GB of RAM. Additional work is required to create the hardware necessary to unwrap the images in near-real-time [41], and to develop approximations to the noise terms to remove the need for multiple image acquisition.…”

Section: Resultsmentioning

confidence: 99%

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Computational signal-to-noise ratio analysis for optical quadrature microscopy

Warger¹,

DiMarzio²

2009

Opt. Express

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Optical quadrature microscopy (OQM) was invented in 1997 to reconstruct a full-field image of quantitative phase, and has been used to count the number of cells in live mouse embryos. Here we present a thorough SNR analysis that incorporates noise terms for fluctuations in the laser, aberrations within the individual paths of the Mach-Zehnder interferometer, and imperfections within the beamsplitters and CCD cameras to create a model for the resultant phase measurements. The current RMS error of the OQM phase images has been calculated to be 0.08 radians from substituting images from the instrumentation into the model.

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Section: Resultsmentioning

confidence: 99%

“…Substituting Eqs. (38)- (41) into Eq. (42) and using Taylor series expansions to remove the denominators provides the reconstructed magnitude and phase induced by the sample:…”

Section: Mathematical Description Of Balanced Mixingmentioning

confidence: 99%

Computational signal-to-noise ratio analysis for optical quadrature microscopy

Warger¹,

DiMarzio²

2009

Opt. Express

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“…The common drawback of these techniques are that they are all iterative algorithms. The number of iterations may be high [ 19 ] and may vary [ 16 , 20 ] depending on the input wrapped phase map. For a realtime DHM, phase unwrapping algorithms with low and constant computational complexities are usually desired for providing fast video rendering with constant frame rate.…”

Section: Introductionmentioning

confidence: 99%

“…A number of implementations for fast phase unwrapping have been proposed [ 19 – 21 ]. The implementations presented in [ 20 , 21 ] are based on PCG [ 13 , 14 ] with field programmable gate array (FPGA) devices and graphic processing unit (GPU) [ 22 ] platforms, respectively. The implementation proposed in [ 19 ] is based on Gauss–Seidel techniques [ 13 , 15 ] with GPU platforms.…”

Section: Introductionmentioning

confidence: 99%

Efficient Phase Unwrapping Architecture for Digital Holographic Microscopy

Hwang

Cheng

2011

Sensors

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This paper presents a novel phase unwrapping architecture for accelerating the computational speed of digital holographic microscopy (DHM). A fast Fourier transform (FFT) based phase unwrapping algorithm providing a minimum squared error solution is adopted for hardware implementation because of its simplicity and robustness to noise. The proposed architecture is realized in a pipeline fashion to maximize throughput of the computation. Moreover, the number of hardware multipliers and dividers are minimized to reduce the hardware costs. The proposed architecture is used as a custom user logic in a system on programmable chip (SOPC) for physical performance measurement. Experimental results reveal that the proposed architecture is effective for expediting the computational speed while consuming low hardware resources for designing an embedded DHM system.

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