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Fundamental limitations of pixel based image deconvolution in radio astronomy

机译:基于像素基于射电天文图像折卷积的基本限制

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Deconvolution is essential for radio interferometric imaging to produce scientific quality data because of finite sampling in the Fourier plane. Most deconvolution algorithms are based on CLEAN which uses a grid of image pixels, or clean components. A critical matter in this process is the selection of pixel size for optimal results in deconvolution. As a rule of thumb, the pixel size is chosen smaller than the resolution dictated by the interferometer. For images consisting of unresolved (or point like) sources, this approach yields optimal results. However, for sources that are not point like, in particular for partially resolved sources, the selection of right pixel size is still an open issue. In this paper, we investigate the limitations of pixelization in deconvolving extended sources. In particular, we pursue the usage of orthonormal basis functions to model extended sources yielding better results than by using clean components.
机译:由于傅立叶平面中的有限采样,解构器对无线电干涉成像产生科学质量数据至关重要。大多数Deconvolution算法基于Clean,它使用图像像素的网格或清洁组件。在该过程中的一个关键问题是选择像素大小以获得去卷积的最佳结果。作为经验法则,选择像素尺寸小于干涉仪决定的分辨率。对于由未解决(或点)组成的图像,该方法产生最佳结果。然而,对于不是像部分解析的来源的不值的来源,右像素大小的选择仍然是一个开放问题。在本文中,我们研究了解压缩扩展源中的像素化的局限性。特别是,我们追求使用正交基本函数来模拟扩展来源,而不是使用清洁部件的延长率。

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