A Fast and Adaptive Imaging Algorithm for the Optical Array Imaging System

Osamu IKEDA

A Fast and Adaptive Imaging Algorithm for the Optical Array Imaging System

Osamu IKEDA

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An optical array imaging system has been presented in previous articles. In this system, first, the object is illuminated with laser light sequentially from each of the array elements and the reflected field is detected as interferogram. The interferograms obtained are then spatially heterodyne-detected on a computer to extract the signal components, that is, array data. Then, the eigenvector of the largest eigenvalue is derived by applying the power method to the array data and it is beam-steered to get images of the object. The algorithm gives good images for most objects, but it fails to work for some objects. It was shown that using a subset of the array data may solve the problem, but that finding the corresponding optimum subaperture is quite time-consuming. In this paper, first, the integral equation describing the system is solved for a general class of object, to make clear the conditions for the eigenvector to form a sharp beam. Second, the imaging algorithm is sped up to a great degree by optimizing only the illuminating aperture in a coarse fashion. Third, the rate of convergence of the power method is adaptively estimated in the algorithm to make the eigenvector derivation reliable. Finally the improved algorithm is investigated using both computer-generated and experimentally obtained array data.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E80-A No.6 pp.1092-1098

Publication Date: 1997/06/25

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Category: Digital Signal Processing

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Osamu IKEDA, "A Fast and Adaptive Imaging Algorithm for the Optical Array Imaging System" in IEICE TRANSACTIONS on Fundamentals, vol. E80-A, no. 6, pp. 1092-1098, June 1997, doi: .
Abstract: An optical array imaging system has been presented in previous articles. In this system, first, the object is illuminated with laser light sequentially from each of the array elements and the reflected field is detected as interferogram. The interferograms obtained are then spatially heterodyne-detected on a computer to extract the signal components, that is, array data. Then, the eigenvector of the largest eigenvalue is derived by applying the power method to the array data and it is beam-steered to get images of the object. The algorithm gives good images for most objects, but it fails to work for some objects. It was shown that using a subset of the array data may solve the problem, but that finding the corresponding optimum subaperture is quite time-consuming. In this paper, first, the integral equation describing the system is solved for a general class of object, to make clear the conditions for the eigenvector to form a sharp beam. Second, the imaging algorithm is sped up to a great degree by optimizing only the illuminating aperture in a coarse fashion. Third, the rate of convergence of the power method is adaptively estimated in the algorithm to make the eigenvector derivation reliable. Finally the improved algorithm is investigated using both computer-generated and experimentally obtained array data.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e80-a_6_1092/_p

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@ARTICLE{e80-a_6_1092,
author={Osamu IKEDA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Fast and Adaptive Imaging Algorithm for the Optical Array Imaging System},
year={1997},
volume={E80-A},
number={6},
pages={1092-1098},
abstract={An optical array imaging system has been presented in previous articles. In this system, first, the object is illuminated with laser light sequentially from each of the array elements and the reflected field is detected as interferogram. The interferograms obtained are then spatially heterodyne-detected on a computer to extract the signal components, that is, array data. Then, the eigenvector of the largest eigenvalue is derived by applying the power method to the array data and it is beam-steered to get images of the object. The algorithm gives good images for most objects, but it fails to work for some objects. It was shown that using a subset of the array data may solve the problem, but that finding the corresponding optimum subaperture is quite time-consuming. In this paper, first, the integral equation describing the system is solved for a general class of object, to make clear the conditions for the eigenvector to form a sharp beam. Second, the imaging algorithm is sped up to a great degree by optimizing only the illuminating aperture in a coarse fashion. Third, the rate of convergence of the power method is adaptively estimated in the algorithm to make the eigenvector derivation reliable. Finally the improved algorithm is investigated using both computer-generated and experimentally obtained array data.},
keywords={},
doi={},
ISSN={},
month={June},}

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TY - JOUR
TI - A Fast and Adaptive Imaging Algorithm for the Optical Array Imaging System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1092
EP - 1098
AU - Osamu IKEDA
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E80-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1997
AB - An optical array imaging system has been presented in previous articles. In this system, first, the object is illuminated with laser light sequentially from each of the array elements and the reflected field is detected as interferogram. The interferograms obtained are then spatially heterodyne-detected on a computer to extract the signal components, that is, array data. Then, the eigenvector of the largest eigenvalue is derived by applying the power method to the array data and it is beam-steered to get images of the object. The algorithm gives good images for most objects, but it fails to work for some objects. It was shown that using a subset of the array data may solve the problem, but that finding the corresponding optimum subaperture is quite time-consuming. In this paper, first, the integral equation describing the system is solved for a general class of object, to make clear the conditions for the eigenvector to form a sharp beam. Second, the imaging algorithm is sped up to a great degree by optimizing only the illuminating aperture in a coarse fashion. Third, the rate of convergence of the power method is adaptively estimated in the algorithm to make the eigenvector derivation reliable. Finally the improved algorithm is investigated using both computer-generated and experimentally obtained array data.
ER -