In the accuracy measurement of phase from interferometers with adjustable fringe contrast, it needs to estimate the contrast of experimental patterns so as to obtain the interference patterns with the maximum contrast. We develop the Fourier-polar transform and combine the directional projection to estimate the global contrast of carrier fringe pattern. The technique is especially used for low-quality fringe pattern such as low contrast and low signal to noise ratio (SNR) that often appear in the interferometric experiment. An illustrative experiment based on the radial shearing interferometer is given. Results generated from this technique are compared with the derived values from theoretical model, and exemplary agreement between both is demonstrated.
In visual detection fields based on line-structured light, the analysis of optical stripe image is a key problem. For the cross-line target image, through measuring the angle between two linear optical stripes the target position or some system’s parameters can be obtained. The traditional technique usually needs many preprocessing steps including image filtering, threshold segmentation, thinning processing and so on. For the images with low signal noise ratio or non-uniform intensity distribution, their application performance will be challenged. Based on the characteristic of translation invariance and rotation synchronization of two-dimensional Fourier transform, the paper combines Fourier transform with polar transform to form new Fourier-polar transform algorithm. It implements the angle measurement in the frequency-domain replaced in the spatial domain. At the same time, to improve the convenient of compute, the polar transform is adopted to calculate the distribution direction of amplitude spectrum energy. The proposed Fourier-polar transform algorithm uses the overall information of the image, and the calculating process is simple and no requirement of image preprocessing. Therefore, it can be applied to measure the angle of cross-line target image in low quality image such as low signal-to-noise ratio or with noise.
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