Efficient implementation of the adaptive scale pixel decomposition algorithm
Efficient implementation of the adaptive scale pixel decomposition algorithm
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DOI：
10.1051/0004-6361/201628596
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发表时间：
2016-06
影响因子：
6.5
通讯作者：
L. Zhang;L. Zhang;S. Bhatnagar;U. Rau;M. Zhang
中科院分区：
文献类型：
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作者：
L. Zhang;L. Zhang;S. Bhatnagar;U. Rau;M. Zhang
上下文在射电天文学中，大多数用于消除望远镜点扩散函数（PSF）影响的流行算法都是CLEAN算法的变体。这些算法中的大多数使用δ函数基来对天空亮度进行建模，这在用于对扩展发射进行成像时导致不期望的伪影。自适应尺度像素分解（Asp-Clean）算法在尺度敏感的基础上对天空亮度进行建模，从而在对包含分辨和未分辨发射的场进行成像时提供显著更好的成像性能。目标。然而，Asp-Clean的运行时成本高于规模不敏感算法。在本文中，我们确定了最昂贵的步骤，在原来的Asp-Clean算法，并提出了一个有效的实现，它显着降低了计算成本，同时保持成像性能与原算法相当。现代宽带望远镜的PSF旁瓣水平显着降低，使我们能够进行近似以降低计算成本，这反过来又允许在合理的时间尺度上对较大图像进行反卷积。方法.与原算法一样，通过函数拟合估计图像中的尺度。在这里，我们介绍了一种分析方法来模拟扩展的排放，和一个修改后的方法来估计用于拟合过程，这最终导致较低的计算成本的初始值。结果新的实现与模拟EVLA数据和成像性能进行了测试，以及与原来的Asp-Clean算法。实验表明，该算法能够以较低的计算代价恢复不同尺度下的特征.
Context. Most popular algorithms in use to remove the effects of a telescope’s point spread function (PSF) in radio astronomy are variants of the CLEAN algorithm. Most of these algorithms model the sky brightness using the delta-function basis, which results in undesired artefacts when used to image extended emission. The adaptive scale pixel decomposition (Asp-Clean) algorithm models the sky brightness on a scale-sensitive basis and thus gives a significantly better imaging performance when imaging fields that contain both resolved and unresolved emission. Aims. However, the runtime cost of Asp-Clean is higher than that of scale-insensitive algorithms. In this paper, we identify the most expensive step in the original Asp-Clean algorithm and present an efficient implementation of it, which significantly reduces the computational cost while keeping the imaging performance comparable to the original algorithm. The PSF sidelobe levels of modern wide-band telescopes are significantly reduced, allowing us to make approximations to reduce the computational cost, which in turn allows for the deconvolution of larger images on reasonable timescales. Methods. As in the original algorithm, scales in the image are estimated through function fitting. Here we introduce an analytical method to model extended emission, and a modified method for estimating the initial values used for the fitting procedure, which ultimately leads to a lower computational cost. Results. The new implementation was tested with simulated EVLA data and the imaging performance compared well with the original Asp-Clean algorithm. Tests show that the current algorithm can recover features at different scales with lower computational cost.