Y. Chen and T.P. Li and M. Wu
High Energy Astrophysics Lab, Institute of High Energy
Physics, Chinese Academy of Sciences, Beijing 100039, PRC
The imaging problem can be described as an optimizing problem in mathematics. Thus the optimizing theory and algorithms can be used to analyse and solve it. In this paper we present a optimizing imaging method, in which we take the imaging problem as an optimizing problem with linear constraints. We choose the objective function carefully. Both the mathematical expectation and the variance of the observed data are considered in it. And the upper and lower limit of the intensity of sources and background can be put in it conveniently. We adopt an algorithm very similar to the affine scaling approach in convex programming. Computer simulations of rotating modulation collimator imaging show that the quality of images from this method is better than that from the traditional cross-correlation method. Both point and extended sources can be imaged in the same field of view. We also apply it to image ROSAT PSPC pointed observation data of Crab. The quality of image is improved significantly. The extended structure of Crab can be seen clearly.