The transmittance of chemical vapor deposition (CVD) ZnS can be effectively improved through the processing of hot isostatic pressing (HIP) in inert gas, especially in the waveband of visible light and near infrared. In general, the size of the particles of the polycrystalline ZnS bulk material can be increased after the processing of HIP. This change can definitely affect the optical properties and mechanical properties of the material. In this paper, a two-step method was applied to improve preparation of transparent polycrystalline ZnS bulk materials. The first step was the growth of polycrystalline ZnS through dynamic CVD. Then the grown polycrystalline ZnS bulk materials was annealed in inert gas at 800~900°C for 10~50 h. Experimental results showed that the optical properties and mechanical properties of the materials have been significantly improved. The average transmission rate of the materials was over 74% in the wavebands 8~12 μm and was over 70% in the mid-infrared 3~5 μm. The absorption peak of the materials at 6 μm attributed to Zn-H complex and S vacancy was obviously decreased. Furthermore, results of imaging experiments showed that lenses made of the annealed transparent polycrystalline ZnS bulk materials has excellent performance in optical properties and modulation transfer function (MTF).
This research aims to study the color distribution of ocean surface over Chinese surrounding sea areas in the CIELAB color space. We measure the spectral reflectance of the East China Sea, the South China Sea and the Philippine Sea by using an underwater vertical profile spectrometer. Based on the standard formula of 1931CIEXYZ tristimulus values, the tristimulus values of the ocean surface color of each sea area were calculated and the ocean surface color were reproduced. The octree color quantization was used to quantify the chromaticity values of each sea area and the main chroma value information distribution of ocean surface was obtained in the CIELAB uniform color space. The obtained results are encouraging in that the chroma information of the ocean surface show differences in different sea areas and have their own characteristics.
KEYWORDS: Neural networks, Visualization, Color difference, Visual process modeling, LCDs, Artificial neural networks, Lithium, Human vision and color perception, Statistical modeling, Standards development
The complexity of cross-media color reproduction is that even the problem of device dependence of color space is solved, color distortion still exists in the different background and viewing condition. In this study, the color characterization for the computer monitor is established with visual matching experiments that based on the color appearance model CIECAM02 and back propagation neural network (BPNN). After analyzing prediction results and the influence of training methods, transfer function, the number of hidden layers and nodes of BPNN, ‘log-sigmoid’ is selected as transfer function, the structure of BPNN is 3-6-6-6-3 in this paper. The average prediction color difference of training samples and test samples are 1.016 and 1.726 respectively within acceptable range of color difference of human vision.
As the development of the polychrome printing technology, more and more pigments are available on printing and packaging industry, which has brought new requirements to the on-line color defect detection for printed matter. There are always difficulties for traditional detecting approaches with commercial RGB cameras to provide competent color resolution due to the color gamut limitation. In this communication, we proposed a snapshot multispectral imaging method using a novel spectral filter array (SFA), which has eight spectral channels and one panchromatic channel. Spectral reconstruction and color reproduction was carried out by using BP network with the training on Munsell colors and typical printed samples. We defined the empirical threshold values for color defect detection in the spectral vector space, and demonstrated the validity of this method with practical printed matter experiments.
In this paper, we reported the laboratory spectral calibration of an ultraviolet (UV) Fourier transform imaging spectrometer (FTIS). A short overview of the designed UV-FTIS, which feature with a Cassegrain objective, an Offner relay optics system and a spatial-and-temporal modulation Michelson structure, is given. The experimental setup of spectral calibration is described, including details of the light source and integrating sphere. A high pressure mercury lamp was used to acquire reference spectrum. We calculated the all optical path difference (OPD) to achieve spectral response of every wavelength sample and divided the position of reference peak to subpixel to increase the precision of spectral calibration. The spectrum of spectral calibration show two weakly responded peaks, which was validated by reference spectrum of fiber optic spectrometer. The deviation of wavelength calibration is low to establish a best spectrometer resolution. The results of spectral calibration can meet the requirements of the UV-FTIS application.
KEYWORDS: Reflectivity, RGB color model, Color difference, Cameras, Digital cameras, Principal component analysis, Imaging systems, Light sources, Optoelectronics, Printing
Spectral reflectance provides the most fundamental information of objects and is recognized as the “fingerprint” of them, since reflectance is independent of illumination and viewing conditions. However, reconstructing high-dimensional spectral reflectance from relatively low-dimensional camera outputs is an illposed problem and most of methods requaired camera’s spectral responsivity. We propose a method to reconstruct spectral reflectance from digital camera outputs without prior knowledge of camera’s spectral responsivity. This method respectively averages reflectances of selected subset from main training samples by prescribing a limit to tolerable color difference between the training samples and the camera outputs. Different tolerable color differences of training samples were investigated with Munsell chips under D65 light source. Experimental results show that the proposed method outperforms classic PI method in terms of multiple evaluation criteria between the actual and the reconstructed reflectances. Besides, the reconstructed spectral reflectances are between 0-1, which make them have actual physical meanings and better than traditional methods.
KEYWORDS: Glucose, Near infrared, Blood, Indium gallium arsenide, Sensors, Absorption, Signal to noise ratio, Fourier transforms, Near infrared spectroscopy, Spectroscopy
Near infrared (NIR) has prospectively applied in non-invasive blood glucose measurement due to glucose absorption among the 1.0-2.5m spectral bands. However, this significant technology is hard to be developed because of other blood components and low signal-to-noise ratio (SNR). In this work, we presented a non-invasive glucose measurement system using Fourier transform spectrometer which will work in fingertips or other human body tissues. A refrigerated InGaAs detector with high quantum efficiency performing well in the range of 1.0-1.7μm wavelength is used to acquire transmissive radiation. Preliminary experiment investigations were set up to test glucose levels of aqueous solutions with different concentrations. The analytical modeling of the interferogram data is based on arithmetic Fourier transform and supported by the curvilineal characterization. Experimental results show the variation of light intensity among different glucose concentrations and emphasize the obvious absorption of glucose in NIR wave-range. This study confirms the suitability that NIR can be developed in non-invasive glucose measurement.
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