将三色图像（JPG）转换为单独的FITS图像

此示例打开一个RGB JPEG图像，并将每个通道作为单独的FITS（图像）文件写出。

此示例使用 pillow 要读图像， matplotlib.pyplot 显示图像，以及 astropy.io.fits 保存配合文件。

By: Erik Bray, Adrian Price-Whelan

许可证：BSD

import numpy as np
from PIL import Image
from astropy.io import fits

设置matplotlib并使用一组更好的绘图参数

import matplotlib.pyplot as plt
from astropy.visualization import astropy_mpl_style
plt.style.use(astropy_mpl_style)

加载并显示原始的3色jpeg图像：

image = Image.open('Hs-2009-14-a-web.jpg')
xsize, ysize = image.size
print(f"Image size: {ysize} x {xsize}")
print(f"Image bands: {image.getbands()}")
ax = plt.imshow(image)

Image size: 232 x 400
Image bands: ('R', 'G', 'B')

分割三个通道（RGB）并将数据作为Numpy数组获取。阵列是扁平的，因此它们是一维的：

r, g, b = image.split()
r_data = np.array(r.getdata()) # data is now an array of length ysize*xsize
g_data = np.array(g.getdata())
b_data = np.array(b.getdata())
print(r_data.shape)

(92800,)

将图像阵列重塑为二维：

r_data = r_data.reshape(ysize, xsize) # data is now a matrix (ysize, xsize)
g_data = g_data.reshape(ysize, xsize)
b_data = b_data.reshape(ysize, xsize)
print(r_data.shape)

(232, 400)

把通道写成单独的FITS图像。添加和可视化标题信息

red = fits.PrimaryHDU(data=r_data)
red.header['LATOBS'] = "32:11:56" # add spurious header info
red.header['LONGOBS'] = "110:56"
red.writeto('red.fits')

green = fits.PrimaryHDU(data=g_data)
green.header['LATOBS'] = "32:11:56"
green.header['LONGOBS'] = "110:56"
green.writeto('green.fits')

blue = fits.PrimaryHDU(data=b_data)
blue.header['LATOBS'] = "32:11:56"
blue.header['LONGOBS'] = "110:56"
blue.writeto('blue.fits')

from pprint import pprint
pprint(red.header)

SIMPLE  =                    T / conforms to FITS standard
BITPIX  =                   64 / array data type
NAXIS   =                    2 / number of array dimensions
NAXIS1  =                  400
NAXIS2  =                  232
EXTEND  =                    T
LATOBS  = '32:11:56'
LONGOBS = '110:56  '

删除创建的文件

import os
os.remove('red.fits')
os.remove('green.fits')
os.remove('blue.fits')