Compression of Optically Encrypted Digital Holograms Using Artificial Neural Networks

Shortt, Alison E.; Naughton, Thomas J.; Javidi, Bahram

doi:10.1109/jdt.2006.884693

Cited by 30 publications

(9 citation statements)

References 54 publications

(56 reference statements)

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“…Recently, the resolution of CCD/CMOS sensors has increased significantly and with it, so, too, has the computational requirement of a digital holographic imaging system. The bandwidth needed for transmission of holograms from one point to another has also increased, and hence compression of digital holograms has been an active area of research [9][10][11][12][13][14][15][16][17][18]. In this context, the quantization of the hologram and the effect on the reconstructed images has been studied before.…”

Section: Introductionmentioning

confidence: 99%

“…In [13], reconstruction from pure phase objects was studied, and perceptible reconstructions were achieved by using a 1 bit (binary) representation level. Various other quantization schemes were developed and studied by Shortt et al [14][15][16]. An in-depth simulation and experimental study on the effect of quantization in phase-shifting digital holography was performed by Mills and Yamaguchi [17], in which the individual phase-shifted interferograms were quantized before calculation of the complex wavefield.…”

Section: Introductionmentioning

confidence: 99%

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Quantization noise and its reduction in lensless Fourier digital holography

Pandey

Hennelly

2011

Appl. Opt.

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Digital holography is an imaging technique that enables recovery of topographic 3D information about an object under investigation. In digital holography, an interference pattern is recorded on a digital camera. Therefore, quantization of the recorded hologram is an integral part of the imaging process. We study the influence of quantization error in the recorded holograms on the fidelity of both the intensity and phase of the reconstructed image. We limit our analysis to the case of lensless Fourier off-axis digital holograms. We derive a theoretical model to predict the effect of quantization noise and we validate this model using experimental results. Based on this, we also show how the resultant noise in the reconstructed image, as well as the speckle that is inherent in digital holography, can be conveniently suppressed by standard speckle reduction techniques. We show that high-quality images can be obtained from binary holograms when speckle reduction is performed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantization noise and its reduction in lensless Fourier digital holography

Pandey

Hennelly

2011

Appl. Opt.

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“…The reader should, therefore, refer to standards of optical JPEG compression [2,3] before attempting an implementation. Indeed, much work has been done toward developing compression methods, most techniques reported, such as presented in [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Optical Image Compression Using a Real Fourier Plane

Alkholidi¹

2013

OPJ

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Hastening transmission by efficiently providing compression is our goal in this work. Image compression consists in reducing information size representing an image. Elimination of redundancies and non-pertinent information enables memory space minimization and thus fast data transmission. Optics can offer an alternative choice to overcome the limitation of numerical compression algorithms. In this paper, we propose real-time optical image compression using a real Fourier plane to save time required for compression by using the principles of coherent optics. Digital and optical simulation results are presented and analyzed. An optical compression decompression setup is demonstrated using two different SLMs (SEIKO and DisplayTech). The purpose of this method is to simplify our earlier method, improve the quality of reconstructed image, and avoid the disadvantages of numerical algorithms.

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“…In Ref. [15] the compression is achieved by non-uniformly quantizing the complex-value encrypted DHs, using an artificial neural network. In the techniques mentioned above, compression factors, ranging from 10 to 100, are reached without losses in the image quality.…”

Section: Introductionmentioning

confidence: 99%

New high compression method for digital hologram recorded in microscope configuration

et al. 2011

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We propose a new method to compress digital holograms (DHs) using a sparse matrix representation. Using digital holography to numerically manage complex wavefields, we are able to apply an adaptive mask, based on a threshold filter, to the object wavefield. From there, we store the result of this filtering by sparse representation. We demonstrate that the proposed sparse representation gives us the possibility to obtain high compression factor with minimal loss in the quality of the reconstructed image. This technique is efficient for storage and transmission of DHs and we propose a multiplexing structure for storage the compressed data.

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Compression of Optically Encrypted Digital Holograms Using Artificial Neural Networks

Cited by 30 publications

References 54 publications

Quantization noise and its reduction in lensless Fourier digital holography

Quantization noise and its reduction in lensless Fourier digital holography

Optical Image Compression Using a Real Fourier Plane

New high compression method for digital hologram recorded in microscope configuration

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