将 MATLAB 绘图转换为图像

发布于 2024-08-15 05:58:27 字数 358 浏览 12 评论 0原文

我已经生成了一个像这样的图

figure; hold;
axis([0 10 0 10]);
fill([ 1 1 5 5], [5 1 1 5],'b')

，现在我想将此图作为矩阵，以便我可以用高斯过滤博客。通过 Google 搜索，我在 MATLAB Central 找到了此线程 Rasterizing Plot to Image。我尝试过，但只能让它适用于线图或函数图。

你有什么想法吗？

原文

I have generated a plot like

figure; hold;
axis([0 10 0 10]);
fill([ 1 1 5 5], [5 1 1 5],'b')

and now I want to have this plot as an matrix so that I can i.e. filter the blog with a gaussian. Googleing I found this thread Rasterizing Plot to Image at MATLAB Central. I tried it, but I could only get it to work for line or function plots.

Do you have any ideas?

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最初的梦 2024-08-22 05:58:27

您可以使用 GETFRAME 函数。它返回电影帧结构，实际上是光栅化的图形。字段 cdata 将包含您的矩阵。

F=getframe;
figure(2)
imagesc(F.cdata);

You can use GETFRAME function. It returns movie frame structure, which is actually rasterized figure. Field cdata will contain your matrix.

F=getframe;
figure(2)
imagesc(F.cdata);

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舟遥客 2024-08-22 05:58:27

您的目标矩阵需要哪些特征？您想要栅格化什么样的图像？

您看，对于您给我们的唯一示例，定义表示图像的矩阵几乎是微不足道的......

1. figmat = ones(10,10,3) % create a 10x10 raster where each entry is a triple for RGB, setting them all to 1 colours the whole raster white
2. figmat(2:5,2:5,1:2) = 0 % sets RG components in the coloured area to 0, leaving only blue

您的矩阵首先是一个栅格。现在，您可以使用内置函数 image 来可视化您的矩阵。查看该函数的文档。请注意，我的建议不符合与 image() 和 colormap() 一起使用的规范。

What are the desired characteristics of your target matrix ? And what sort of images do you want to rasterise ?

You see, for the only example you have given us it's almost trivial to define a matrix representing your image ...

1. figmat = ones(10,10,3) % create a 10x10 raster where each entry is a triple for RGB, setting them all to 1 colours the whole raster white
2. figmat(2:5,2:5,1:2) = 0 % sets RG components in the coloured area to 0, leaving only blue

Your matrix is a raster to start with. Now, you can use the built-in function image to visualise your matrix. Have a look at the documentation for that function. And note that my suggestion does not meet the spec for use with image() and colormap().

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