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- 저자 : PHAN HUY PHUC (검색결과 1 건)
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Improved wavefront reconstruction algorithm for freeform measurement : 자유곡면 측정을 위한 파면재구성 알고리즘의 개선
PHAN HUY PHUC University of Science and Technology 2017 국내석사
With the development of optical systems that used to evaluate the freefrom surface such as lateral shearing interferometer (LSI), deflectometry, and the Shack - Hartmann sensor, the demand of supporting algorithms has risen. They are phase unwrapping algorithm that estimates the absolute (true) phase from the wrapped (measured, principle) phase taken from some captured fringe images, followed by some steps to give the slope measurment data of the surface; then we need a wavefront reconstruction algorithm to reconstruct the surface from these slope data. We propose a wavefront reconstruction algorithm from slope measurements based on a zonal method. In this algorithm, the slope measurement sampling geometry used is the Southwell geometry, in which the phase values and the slope data are measured at the same nodes. The proposed algorithm estimates the phase value at a node point using the slope measurements of eight points around the node, as doing so is believed to result in better accuracy with regard to the wavefront. For optimization of the processing time, a successive over-relaxation method is applied to iteration loops. We use a trial-and-error method to determine the best relaxation factor for each type of wavefront in order to optimize the iteration time and, thus, the processing time of the algorithm. Specifically, for a circularly symmetric wavefront, the convergence rate of the algorithm can be improved by using the result of a Fourier Transform as an initial value for the iteration. Various simulations are presented to demonstrate the improvements realized when using the proposed algorithm. Several experimental measurements of deflectometry are also processed by using the proposed algorithm. Considering PUMA algorithm as one of the most efficient phase unwrapping algorithm with the ability to process various type of phase at high accuracy. However, the drawback of the PUMA lies on computation speed when processing large, complex phase, and the lack of pre-filter make trouble for PUMA processing noisy data. In this paper, we proposed a new algorithm compounding two structures: the incremental breadth-first search (IBFS) which modifies Boykov-Kolmogorov (BK) in the way finding path from source to sink of a graph in max-flow problem in order to help reduce processing time of PUMA algorithm; and a pre-filter by principle of adaptive local denoising. Simulations and experimental implementation used to demonstrate ability of the proposed algorithm.
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