Two-dimensional spectral image calibration based on feed-forward neural network

In this paper, we present a novel method on image calibration, utilizing Total Least Square (TLS) method and Feedforward Neural Network, to solve the aberration problem of LAMOST two-dimensional astronomical spectral images. In our method, training sample set is generated with domain knowledge, from which a number of discrete points are are extracted from spectral images with fiber tracing method, and output vectors are formed by the corresponding calibrated points, obtained by utilizing the TLS method. The Feed-forward Neural Network is trained to obtain the transformation matrix, casting about for the matching relationship between the input and output sets. We also perform comparative experiments on fiber tracing and spectrum extraction results between calibrated spectral images and uncalibrated spectral images, the results show an advantage of higher accuracy and precision by our proposed method.