It should be possible to do this through PIL. Here is a rough outline of the steps:
1) Load the image and convert to numpy array
im = Image.open('myimage.png').convert('RGBA')
matrix = numpy.array(im)
2) Modify the matrix in place. The matrix is a list of lists of the pixels within each row. Pixels are represented as [r, g, b, a]. Write your own function to convert each [r, g, b, a] pixel to the [r, g, b] value you desire.
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根据要求使用 ImageMagick：
感谢@mf511 的更新。
Using ImageMagick, as requested:
Thanks @mf511 for the update.
cssndrx 答案的更完整版本，使用 numpy 中的切片来提高速度：
等等瞧！
A more complete version of the cssndrx answer, using slicing in numpy to improve speed:
Et voila !
我刚刚发布了一些 Python 和 C 代码，可以满足您的需求。它在github上： http://github.com/maxme/PNG-Alpha-Premultiplier
Python 版本基于 cssndrx 响应。 C版本基于libpng。
I just released a bit of code in Python and in C that does what you are looking for. It's on github: http://github.com/maxme/PNG-Alpha-Premultiplier
The Python version is based on the cssndrx response. C version is based on libpng.
通过 PIL 应该可以做到这一点。以下是步骤的粗略概述：
1) 加载图像并转换为 numpy 数组
2) 修改矩阵。该矩阵是每行内像素列表的列表。像素表示为 [r, g, b, a]。编写您自己的函数将每个 [r, g, b, a] 像素转换为您想要的 [r, g, b] 值。
3）使用将矩阵转换回图像
It should be possible to do this through PIL. Here is a rough outline of the steps:
1) Load the image and convert to numpy array
2) Modify the matrix in place. The matrix is a list of lists of the pixels within each row. Pixels are represented as [r, g, b, a]. Write your own function to convert each [r, g, b, a] pixel to the [r, g, b] value you desire.
3) Convert the matrix back to an image using
仅使用 PIL：
Using PIL only: