KEYWORDS: Digital signal processing, Fiber optics sensors, Optical fibers, Sensors, Signal detection, Detection and tracking algorithms, Signal processing, Interferometers, Sensing systems, Optical sensing
A positioning system based on Mach-Zehnder optical fiber interferometer is proposed, which can sense vibration
information along the circumference of the fiber sensor and hence be applied to positioning invasions as a safe-guard
system in residence communities. A cross-correlation algorithm fulfilled with a DSP processor has been adopted to
calculate the time difference of two channels of the Mach-Zehnder optical fiber interferometer. A signal identification
algorithm is proposed to decrease the workload of the DSP when no vibration occurs. An experiment with 11.28
kilometers sensing fiber has been carried out, whose results show the Mach-Zehnder positioning system identifies the
position of vibration instantaneously and has a 44 meters positioning error within the total sensing distance.
In the case of optical computed tomography (OpCT) reconstructions for the field comprising obstacle objects, parts of the projection data are lost; hence, the image reconstruction would be always imprecise with conventional OpCT algorithms if no other preprocessing or interpolation approaches are adopted. To solve the problem of the reconstruction with incomplete data, a Lagrange interpolation reprojection-revising (LIRR) algorithm is proposed. First a Lagrange interpolation polynomial is adopted to preestimate the lost projection data. By comparing to the reprojection of the rough reconstructed image in the iteration, the unbiased Lagrange interpolation estimations are retained; otherwise, the biased estimations are revised, ray by ray, with the weighed superposition of the interpolation and the reprojection data. These steps are repeated until all estimations for lost data are acceptable. Reconstruction results of some known algorithms and the LIRR algorithm for two typical tested images, including a circle round opaque object, were compared. Additionally, an emission spectral tomography experiment was also designed to evaluate the LIRR. The simulation and experiment results show the LIRR makes a great improvement in reconstruction precision over the traditional OpCT algorithms and hence has potential application of OpCT reconstructions with incomplete data.
A new approach combining a discrete iterative reconstruction-reprojection algorithm (DIRR) with a finite impulse response (FIR) low-pass filter is proposed for reconstructing images comprising opaque objects in optical computed tomography (CT). This filter, employing a rectangular window function and various bandwidths, is adopted to smooth the reprojection data between iterative reconstruction and reprojection stages. Compared reconstruction results of the traditional iterative reconstruction-reprojection (IRR) algorithm, projection space iteration reconstruction-reprojection (PSIRR) algorithm, and the new DIRR algorithm for an asymmetrical four-peak and a single-peak test image, including a circle round opaque object, are studied. The results show that the reconstruction precision of the new algorithm is related to the value of the bandwidth of the finite impulse response (FIR) filter, and the optimal bandwidth increases when the space frequency of the reconstructed image ascends. Furthermore, the DIRR algorithm with an optimal bandwidth has an obviously higher reconstruction precision than IRR and PSIRR algorithms, and has a potential application of reconstructing images, including obstacle objects with limited views.
A series of image processing methods of fringe analysis is given, which is important for the interference fringes. Through image smoothing course such as homomorphic filtering and thresholding, then thinning, disbranching with chain, fitting, a single-pixel fringe can be obtained, which will be prepared for the coming computing the tested parameters. All which have been proved by experiments.
Some approaches, which include iterative reconstruction-reprojection (IRR), projection space iteration reconstruction-reprojection (PSIRR) and other interpolation methods, have already been proposed for the reconstruction of fields including opaque objects. In the IRR, the interpolation operation is performed in the object space during backprojection-reprojection. The errors associated with the interpolation degrade the reconstructed image and may cause divergence unless a large number of rays and views are adopted. In the research of optical test, the testing views are often limited; therefore, the results are usually poor when using the IRR to reconstruct the fields including opaque objects. To improve the reconstruction precision in this case, a new approach is proposed, which is based on the discrete IRR algorithm and the finite impulse response (FIR) lowpass filer (DIRRLF). This filer is used to process the reprojection data between the iterative reconstruction and the reprojection stages. Different window functions and bandwidths are adopted for the lowpass filter. The compared reconstruction results of discrete IRR algorithm and DIRRLF algorithm for an asymmetrical single-peak simulation field including a circle round opaque object are studied with the numerical simulation of computer. The results show that this algorithm has higher reconstruction precision than the discrete IRR algorithm and has a potential application of reconstructing real three-dimensional fields including opaque objects.
A novel self-adaptive volume reconstruction technique (SVRT) based on multiobjective optimization is proposed. Its reconstruction results for asymmetrical 3-D single-peak cosine emission coefficient fields are studied with the numerical simulation of a computer. The results show that this algorithm has faster convergences and higher reconstruction precision, and can reconstruct asymmetrical single-peak cosine emission coefficient fields perfectly with only two views. (The average error is 0.18% with no noise data.) In the experiment of argon-arc plasma diagnosis, the 3-D reconstructions of temperature and ionization coefficient fields are fulfilled with this algorithm combined with the spectrum relative-intensity method.
Optical Computed Tomography is a useful tool for plasma diagnostics. But in plasma physics, viewing access is very limited, which leads a highly undetermined inversion problem. Two major approaches to this problem are compared in this paper: Maximum Entropy (ME) method and Simultaneous Iterative Reconstruction Technique (SIRT). The results of numerical simulation and experiments illustrate that both two algorithms can yield good qualities of reconstruction with limited views when some prior information has incorporated into calculation. Especially, in the case of two views, with prior information, a good result can even be achieved by ME algorithm.
In this paper, we consider a promising method of pattern recognition based on Texture Features (TF) to classify cancer cell. With this technique, the TF characters are calculated among different cells or different regions of cells. Then these texture features are transmitted to the input neurons of the Back Propagation (BP) neural network. After training phase of neural network, the structure is determined. At last, we design an opto-electronic neural network to complete the cancer cells recognition.
In the testing and control of electricity system, Magnetism-photo optical fiber electricity sensor modules based on Faraday Effect of the main electricity wire can be made. We can play these sensor modules at the spots where the electricity need to be tested and controlled real-timely and make use of the Wavelength Division Multiplexing (WDM) technique of optical fiber network to transmit the real time data from all spots to the central computer, so the system of distributed optical fiber electricity current supervision and control is constructed.
KEYWORDS: Holograms, Signal to noise ratio, Refractive index, Water, Modulators, Image quality, Temperature metrology, Californium, Holography, Signal processing
The experiment has indicated in this paper that dichromated gelatin (DCG) holograms after the first development can be reprocessed. The quality of over exposed of multi-exposed DCG holograms can be improved by reprocessing. This is especially beneficial for the DCG hologram with short developed time in the first development processing.
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