A Comparison of the MEM and the MP-CLEAN Methods for the Image Reconstruction of Extended Sources with Simulated Visibility Data

In the radio synthesis imaging area,the deconvolution is used to fill up the un-sampled points at the Fourier domain.The algorithms like CLEAN and MEM often play an important role in the deconvolution.As extended sources have more complex visibility,the reconstruction for extended sourcesis difficult.In this paper we make a comparison of the MEM(Maximum Entropy Method) with the speed up CLEAN method(named Multi-Point CLEAN in this paper,or MP-CLEAN for short) for extended source reconstruction based on the simulated visibility data.The simulated data are produced by sampling the Flourier Frequency domain for a true image with the sample function generated from a simulated interferometer array.By analyzing and comparing,it is easy to find that both of these two methods work well on the image reconstruction while the MP-CLEAN is better than the MEM for getting rid of the side lobes.The MP-CLEAN is at least 3 times faster than the MEM in our simulations.A deeper analyzing of the selection of parameters shows that the MEM is more independent on the parameters than the MP-CLEAN,which indicates that the MEM is more robust.