Optical data processing and filtering systems

Cutrona, Louis J.; Leith, Emmett N.; Palermo, C. J.; Porcello, L. J.

doi:10.1109/tit.1960.1057566

Cited by 306 publications

(66 citation statements)

References 4 publications

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“…These methods were independently developed by Wiley at the Goodyear Aircraft Company [75] and Sherwin et al at the University of Illinois at Urbana-Champaign in the 1960s [76]. Interestingly, as the digital computational power at that time was far from sufficient for processing radar data, Fourier optical methods were used for radar data processing [77][78][79]. Further insightful comparisons and connections between SAR and ISAM were discussed in Ref [74].…”

Section: Interferometric Synthetic Aperture Microscopymentioning

confidence: 99%

Computational optical coherence tomography [Invited]

Liu

South

et al. 2017

Biomed. Opt. Express

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Optical coherence tomography (OCT) has become an important imaging modality with numerous biomedical applications. Challenges in high-speed, high-resolution, volumetric OCT imaging include managing dispersion, the trade-off between transverse resolution and depth-of-field, and correcting optical aberrations that are present in both the system and sample. Physics-based computational imaging techniques have proven to provide solutions to these limitations. This review aims to outline these computational imaging techniques within a general mathematical framework, summarize the historical progress, highlight the state-of-the-art achievements, and discuss the present challenges. Swanson, "Optical biopsy and imaging using optical coherence tomography," Nat. Med. 1(9), 970-972 (1995). 3. G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, "In vivo endoscopic optical biopsy with optical coherence tomography," Science 276(5321), 2037-2039 (1997). 4. S. A. Boppart, B. E. Bouma, C. Pitris, J. F. Southern, M. E. Brezinski, and J. G. Fujimoto, "In vivo cellular optical coherence tomography imaging," Nat. Med. 4(7), 861-865 (1998). Sundaram, P. S. Ray, and S. A. Boppart, "Real-time imaging of the resection bed using a handheld probe to reduce incidence of microscopic positive margins in cancer surgery," Cancer Res. 75(18), 3706-3712 (2015). 9. J. G. Fujimoto and E. A. Swanson, "The development, commercialization, and impact of optical coherence tomography," Invest. Ophthalmol. Vis. Sci. 57(9), OCT1-OCT13 (2016). 10. A. M. Cormack, "Representation of a function by its line integrals, with some radiological applications. II," J.Appl. Phys. 35(10), 2722-2727 (1964). 11. G. N. Hounsfield, "Computerized transverse axial scanning (tomography). 1. Description of system," Br. J.Radiol. 46(552), 1016-1022 (1973). 12. P. C. Lauterbur, "Image formation by induced local interactions: examples employing nuclear magnetic resonance," Nature 242(5394), 190-191 (1973). 13. P. T. Gough and D. W. Hawkins, "Unified framework for modern synthetic aperture imaging algorithms," Int. J.Imaging Syst. Technol. 8(4), 343-358 (1997). shaping for optimal depth-selective focusing in optical coherence tomography," Opt. Express 21(3), 2890-2902 (2013 111-115 (1962). 77. L. Cutrona, E. Leith, C. Palermo, and L. Porcello, "Optical data processing and filtering systems," IRE Trans.Inf. Theory 6(3), 386-400 (1960). 78. L. J. Cutrona, E. N. Leith, L. J. Porcello, and E. W. Vivian, "On the application of coherent optical processing techniques to synthetic-aperture radar," Proc. IEEE 54(8), 1026-1032 (1966). 79. W. Brown and L. Porcello, "An introduction to synthetic-aperture radar," IEEE Spectr. 6(9), 52-62 (1969). 80. M. P. Hayes and P. T. Gough, "Broad-band synthetic aperture sonar," IEEE J. Oceanic Eng. 17(1), 80-94 (1992)

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Section: Interferometric Synthetic Aperture Microscopymentioning

confidence: 99%

Computational optical coherence tomography [Invited]

Liu

South

et al. 2017

Biomed. Opt. Express

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“…This concept is called spatial (frequency) filtering [8][9][10][11][12][13][14], it is a generalisation that encompasses convolution and correlation operations, and it could be performed over 2D images in constant time while limited in speed only by the refresh rates of the input and output devices.…”

Section: Optical Pattern Recognitionmentioning

confidence: 99%

Phase in Optical Image Processing

Naughton¹,

Rastogi²,

Hack³

2010

AIP Conference Proceedings

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Abstract. The use of phase has a long standing history in optical image processing, with early milestones being in the field of pattern recognition, such as VanderLugt's practical construction technique for matched filters, and (implicitly) Goodman's joint Fourier transform correlator. In recent years, the flexibility afforded by phase-only spatial light modulators and digital holography, for example, has enabled many processing techniques based on the explicit encoding and decoding of phase. One application area concerns efficient numerical computations. Pushing phase measurement to its physical limits, designs employing the physical properties of phase have ranged from the sensible to the wonderful, in some cases making computationally easy problems easier to solve and in other cases addressing mathematics' most challenging computationally hard problems. Another application area is optical image encryption, in which, typically, a phase mask modulates the fractional Fourier transformed coefficients of a perturbed input image, and the phase of the inverse transform is then sensed as the encrypted image. The inherent linearity that makes the system so elegant mitigates against its use as an effective encryption technique, but we show how a combination of optical and digital techniques can restore confidence in that security. We conclude with the concept of digital hologram image processing, and applications of same that are uniquely suited to optical implementation, where the processing, recognition, or encryption step operates on full field information, such as that emanating from a coherently illuminated real-world three-dimensional object.

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“…INTRODUCTION Diffraction is caused by an obstacle placed in the path of a plane wave of monochromatic light [1,2,3]. The diffraction pattern formed at an infinite distance has the distribution of the Fourier transform of the geometry of the obstacle.…”

Section: Noticementioning

confidence: 99%

Time-Frequency Signatures Through Optical Diffraction Scanning

Jackson¹

1963

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Optical data processing and filtering systems

Cited by 306 publications

References 4 publications

Computational optical coherence tomography [Invited]

Computational optical coherence tomography [Invited]

Phase in Optical Image Processing

Time-Frequency Signatures Through Optical Diffraction Scanning

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