摘要：We present a two-channel deconvolution method that decomposes images into a parametric point-source channel and a pixelized extended-source channel. Based on the central idea of the deconvolution algorithm proposed by Magain et al. (1998, ApJ, 494, 472), the method aims at improving the resolution of the data rather than at completely removing the point spread function (PSF). Improvements over the original method include a better regularization of the pixel channel of the image, based on wavelet filtering and multiscale analysis, and a better controlled separation of the point source vs. the extended source. In addition, the method is able to simultaneously deconvolve many individual frames of the same object taken with different instruments under different PSF conditions. For this purpose, we introduce a general geometric transformation between individual images. This transformation allows the combination of the images without having to interpolate them. We illustrate the capability of our algorithm using real and simulated images with complex diffraction-limited PSF.
