Fused CLEAN deconvolution for compact and diffuse emission
Fused CLEAN deconvolution for compact and diffuse emission
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DOI：
10.1051/0004-6361/201833090
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发表时间：
2018-10
影响因子：
6.5
通讯作者：
L. Zhang
中科院分区：
文献类型：
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作者：
L. Zhang
上下文CLEAN算法是优秀的反卷积求解器，它可以去除脏波束的旁瓣，以清洁脏图像。从规模的角度来看，有两种类型：规模不敏感的CLEAN算法和规模敏感的CLEAN算法。尺度不敏感的CLEAN算法对于紧凑发射表现得非常好，而对于漫射发射表现得很差，而尺度敏感的CLEAN算法对于点状发射和漫射发射都很好，但通常计算昂贵。然而，观察到的图像通常包含紧凑和漫射发射。因此，需要一种可以同时处理紧凑和漫射发射的算法。目标。我们提出了一种新的反卷积算法结合规模不敏感的CLEAN算法和规模敏感的CLEAN算法。新算法结合了压缩发射的尺度不敏感算法和扩散发射的尺度敏感算法的优点。同时，它避免了尺度不敏感算法对漫射发射的性能差和尺度敏感算法对残差中紧凑发射的计算量大。方法.我们提出了一种融合机制来结合联合收割机两种算法：Asp-Clean 2016算法，它解决了拟合过程中卷积运算的计算开销问题，以及经典的Högbom CLEAN（Hg-Clean）算法，该算法速度更快，适用于紧凑型发射。本文称之为Fused-Clean（熔融清洁）。结果我们将融合清洁算法应用于模拟EVLA数据，并将其与广泛使用的算法进行比较：Hg-Clean算法，多尺度CLEAN（Ms-Clean）和Asp-Clean 2016算法。结果表明，它的性能更好，是计算有效的。
Context. CLEAN algorithms are excellent deconvolution solvers that remove the sidelobes of the dirty beam to clean the dirty image. From the point of view of the scale, there are two types: scale-insensitive CLEAN algorithms, and scale-sensitive CLEAN algorithms. Scale-insensitive CLEAN algorithms perform excellently well for compact emission and perform poorly for diffuse emission, while scale-sensitive CLEAN algorithms are good for both point-like emission and diffuse emission but are often computationally expensive. However, observed images often contain both compact and diffuse emission. An algorithm that can simultaneously process compact and diffuse emission well is therefore required. Aims. We propose a new deconvolution algorithm by combining a scale-insensitive CLEAN algorithm and a scale-sensitive CLEAN algorithm. The new algorithm combines the advantages of scale-insensitive algorithms for compact emission and scale-sensitive algorithms for diffuse emission. At the same time, it avoids the poor performance of scale-insensitive algorithms for diffuse emission and the great computational load of scale-sensitive algorithms for compact emission in residuals. Methods. We propose a fuse mechanism to combine two algorithms: the Asp-Clean2016 algorithm, which solves the computationally expensive problem of convolution operation in the fitting procedure, and the classical Högbom CLEAN (Hg-Clean) algorithm, which is faster and works equally well for compact emission. It is called fused CLEAN (fused-Clean) in this paper. Results. We apply the fused-Clean algorithm to simulated EVLA data and compare it to widely used algorithms: the Hg-Clean algorithm, the multi-scale CLEAN (Ms-Clean), and the Asp-Clean2016 algorithm. The results show that it performs better and is computationally effective.