Wave-front aberration modeling based on wavelet methods

Wave-front aberration has serious adverse influence on the efficiency of optical system whose modeling problem is of great importance for further research. In this paper, wavelet method, which has a broad application in signal analysis, is used to model wave-front aberration. As the basis of wavelet method, the selection of basis function is the primary step for signal reconstruction, and two types of wave-front aberration are studied in this paper. First, for general wave-front aberration, a selection algorithm is given by comparing the minimum Mean Square Error (MSE).Secondly we take into account the primary wave-front aberration represented by finite Zernike polynomials, a simplified selection algorithm is proposed via minimum Maximum Mean Error Ratio (MMER) criterion. Numerical results shows that basis function selection algorithm via minimum MMER criterion can ensure the modeling accuracy, and it costs much smaller calculation than minimum MSE criterion.