Drizzle: A method for the linear reconstruction of undersampled images
Drizzle: A method for the linear reconstruction of undersampled images
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DOI：
10.1086/338393
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发表时间：
2002-02-01
影响因子：
3.5
通讯作者：
Hook, RN
中科院分区：
文献类型：
--
作者：
Fruchter, AS;Hook, RN
我们已经开发了一种方法，用于从欠采样，抖动数据的图像的线性重建。该算法被称为可变像素线性重建（Variable-Pixel Linear Reconstruction），或非正式地称为“Drizzle”，保留了光度和分辨率，可以根据每个像素的统计显著性对输入图像进行加权，并消除几何失真对图像形状和光度的影响。本文介绍了该方法及其实现。讨论了该算法的测光和天体测量精度、图像保真度以及输出图像的噪声特性。此外，我们描述了使用毛毛雨的联合收割机抖动图像中存在的宇宙射线。
We have developed a method for the linear reconstruction of an image from undersampled, dithered data. The algorithm, known as Variable-Pixel Linear Reconstruction, or informally as "Drizzle," preserves photometry and resolution, can weight input images according to the statistical significance of each pixel, and removes the effects of geometric distortion on both image shape and photometry. This paper presents the method and its implementation. The photometric and astrometric accuracy and image fidelity of the algorithm as well as the noise characteristics of output images are discussed. In addition, we describe the use of drizzling to combine dithered images in the presence of cosmic rays.