A method of measuring water colority based on HSV chromaticity (H hue, S saturation, V value) system is proposed. The measurement system is composed of halogen lamp, sample cell and spectrometer. The spectrum data of transmission light captured by spectrometer is used to calculate the XYZ tristimulus values which is then converted to HSV chromaticity. The colority and saturation value shows a good functional relationship which is calibrated in the experiment. Therefore the water colority can be calculated by the saturation in the HSV chromaticity. Since the hue value is acquired at the same time, the method can be adopted to test water sample with different hue. Moreover, the V value is an independent component, so the instability of light source has no influence on the measurement. The colority obtained by the calibrated function coincides with the standard solution.
The phase diversity wave-front sensing (PDWFS) technique is a posteriori image-based wave-front sensing method which utilizes two images collected simultaneously whose pupil phase differs from each other in a known manner, typically the defocus phase diversity. Here, we present a new method of implementing phase diversity on the sparse aperture imaging system that adds an intentional piston phase to one subaperture. The objective function is firstly derived for the sparse aperture imaging system, then the genetic algorithm is used to minimize the objective function to estimate the piston errors of the subapertures. Digital simulations are conducted for varying amounts of piston phase diversity and levels of noise, the performance of sub-aperture phase diversity is evaluated by comparing with the conventional defocus phase diversity. The results show that the conventional defocus phase diversity performs better than the sub-aperture phase diversity when there is no noise, while the sub-aperture phase diversity outperforms the conventional defocus phase diversity when the noise strength increases. Sub-aperture phase diversity may be an useful alternative if the conventional defocus phase diversity method fails.
In order to eliminate the noise in images acquired by the sparse aperture system, the modeling and filtering of electrical and optical noise are analyzed by the case of three-mirror aperture optical system. The study shows that the median filter can be applied to remove Gauss and salt & pepper noise, meanwhile high-pass filter with Gauss function can eliminate the influence of non-uniform illuminating on imaging. The Lucy-Richardson algorithm is used to restore the image, by which the resolution is heightened.
The phase diversity wavefront sensing (PDWFS) technique is an a posteriori image-based wavefront sensing technique which has been successfully implemented to the Hubble Space Telescope. The analytical form for the phase diversity Cramér-Rao lower bound(CRLB) of Golay3 aperture is firstly derived. Monte Carlo analysis of the PDWFS CRLB is used due to the dependence of CRLB on the true values of aberration parameters being estimated. Then the ensemble average of mean-squared errors(MSE) quantities of CRLB is used to evaluate the performance of imaging schemes with different photon distributions and different amounts of defocus. The numerical simulation shows that for a point source target, if a third image implies the inclusion of extra photons, the MSE would be reduced to a degree in accordance with the amount of the extra photons, the MSE remains nearly unchanged if the totoal photons is finite, no matter for a two-channel or a three-channel system. We also find that varying the defocus of one image becomes meaningless if the defocus of the other image is at a high level.