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Multi-resolution Image Registration Algorithm (MIRA): Robust Automated Image Registration Using Python

机译:多分辨率图像配准算法(MIRA):使用Python的强大自动图像注册

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A primary problem with combining images taken at different epochs is the difficulty in determining the offset between the images in an automated manner. Automated multi-scale techniques have been adopted for use in aligning images taken with ground-based telescopes with great success. However, several characteristics of Hubble Space Telescope (HST) images made direct application of the ground-based multi-scale techniques problematic. This paper describes how an algorithm developed for automated image alignment of Earth observing satellite imagery was merged with a multi-scale analysis of the images to produce a new image registration task. This task was developed using Python, with C extensions for efficiency, and has undergone initial testing to successfully align HST images of the core of 47Tuc and, separately, mosaics of HST images of the Orion Nebula without any differences in the parameter settings. More work needs to be done to improve the run time and to generalize it to work on non-HST images before making it publicly available on all platforms which run Python.
机译:在不同时期拍摄的图像组合图像的主要问题是难以以自动方式确定图像之间的偏移。已经采用自动多尺度技术用于对准与地面望远镜拍摄的图像以巨大的成功进行对齐。然而,哈勃太空望远镜(HST)图像的几个特性直接应用了基于地面的多尺度技术问题。本文介绍了如何为地球自动图像对齐开发的算法与图像的多尺度分析合并,以产生新的图像配准任务。此任务是使用Python开发的,使用C扩展效率,并且经历了初始测试,以成功将47Tuc的核心的HST图像与Orion Nebula的HST图像分别的Mosaics对齐,而没有参数设置的任何差异。需要做更多的工作来改进运行时,并概括它在公开可在运行Python的所有平台上进行公开使用,以概括为非HST图像。

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