问题描述
我在python中有5个天文学图像，每个图像都具有不同的波长，因此它们具有不同的角分辨率和栅格大小，并且为了进行比较，以便创建温度图，我需要它们具有相同的角分辨率，网格大小.
I have 5 astronomy images in python, each for a different wavelength, therefore they are of different angular resolutions and grid sizes and in order to compare them so that i can create temperature maps i need them to be the same angular resolution and grid size.
我已经设法使高斯将每张图像卷积到与最差的图像相同的角分辨率，但是我在寻找一种方法来在python中重新栅格化每张图像时遇到困难，并且想知道是否有人知道该怎么做?
I have managed to Gaussian convolve each image to the same angular resolution as the worst one, however i am having trouble finding a method to re-grid each image in python and wondered if anyone knew how to go about doing this?
我希望将图像重新网格化为与最差质量图像相同的网格大小，因此如果需要，我可以将其用作参考图像.谢谢
I wish to re-grid the images to the same grid size as the worst quality image and so i can use that as a reference image if required. Thank you
推荐答案
如果图像标题具有正确的世界坐标系数据，则可以使用reproject包对图像进行重新采样: http://reproject.readthedocs.org/en/stable/
If the image headers have the correct World Coordinate System data, you can use the reproject package to resample the images: http://reproject.readthedocs.org/en/stable/
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