从 2D 图像获取 3D 图像
我正在 Matlab 中做一个关于图像处理的项目
是否有可能从 2d 图像获取 3d 图像？
I am doing a project in Matlab on Image processing
Is there any possibility of getting 3d image from 2d image?
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如果您有同一物体的多张图像以及拍照时相机的位置，那么这是可能的，但仍然不容易。您可以在此处找到两个此类数据集和相关文章的链接：http://vision.middlebury.edu/mview/< /a>
If you have multiple images of the same object and the position of the camera when the picure was taken, then it is possible, but still not easy. You can find two such datasets and links to relevant articles here: http://vision.middlebury.edu/mview/
3D 图像将是 4D 的投影（并显示您必须投影到 2D 的图像之一），并且由于这种投影，可以在计算机或相框中显示的大多数图像都是 3D 对象的 2D 投影事实上，它选择了高维空间的一个切片，它不包含反转该投影并从 2d 图像返回 3d 所需的信息，
但如果您对空间有足够的采样，则可以从 3d 对象重建它的二维图像，但我不知道有什么简单的方法可以做到这一点
a 3d image would be a projection from 4d (and to show one of those you've got to project down to 2d) and most images that can be displayed on computer or in a picture frame are 2d projections of 3d objects due to this projection which in fact selects a slice of the higher dimensional space it doesn't contain the information needed to invert that projection and get back to 3d from a 2d image
but if you have sufficient sampling of the space it is possible to reconstruct a 3d object from 2d images of it but i don't know of any simple ways to do this
如果不支持数据（例如描述同一 3D 对象的多个 2D 图像），您就无法做到这一点。然后，您需要找出拍摄每个图像的视角，将它们协调到真实空间中，并使用诸如通过每个图像平面的立体线相交到相同物理坐标上的方法生成点。
您还可以通过利用单个图像中的照明数据来尝试超像素方法，尽管这些方法并不那么准确。
这是一个很大的领域。
You can't do this without supporting data such as multiple 2D images describing the same 3D object. You then need to figure out the perspectives from which each image was taken, reconcile those into real space, and generate your points using a method such as intersection of stereo lines through each image plane onto the same physical coordinate.
You can also attempt a superpixel approach by exploiting lighting data within a single image, though these methods aren't as accurate.
This is a big field.
Radon 变换 在断层扫描应用中用于从许多 2D 投影重建 3D 表示（即图像） 3D“场景”。该变换及其逆变换存在于 Matlab 的图像处理工具箱中。您可能想看一下。
希望这有帮助。
一个。
The Radon transform is used in tomography applications to reconstruct 3D representations (i.e.images) from many 2D projections of the 3D "scene". This transform and its inverse are present in the image processing toolbox of Matlab. You might want to have a look at it.
Hope this helps.
A.