缝合微芯片的显微镜图像 [英] stitching microscope images of a microchip

问题描述

因此，我正在尝试缝合微芯片显微镜拍摄的图像，但是要对齐所有功能非常困难.我已经在两张相邻的图像之间有50％的重叠，但是即使那样，它也不总是很合适.

So, I'm trying to stitch images taken by a microscope of a microchip, but it's very hard to have all the features aligned. I already have a 50% overlap between two adjacent images, but even with that, it's not always a good fit.

我正在将SURF与OpenCV一起使用以提取关键点并找到单应矩阵.但这仍然远远不能令人满意.

I'm using SURF with OpenCV to extract the keypoints and find the homographic matrix. But still, it's far from being an acceptable result.

我的目标是能够完美地缝合2x2图像，因此，我可以递归地重复该过程，直到获得最终图像为止.

My objective is to be able to stitch perfectly 2x2 images, so this way, I can repeat that process recursively until I have the final image.

您有什么建议吗?一个解决该问题的好算法.或者也许是一种转换图像的方法，以便能够从图像中提取更好的关键点.发挥阈值(较小的阈值以获得更多的关键点，还是较大的阈值?).

Do you have any suggestion ? A nice algorithm to approach this problem. Or maybe a way to transform the images to be able to extract better keypoints from them. Play with the threshold (a smaller one to get more keypoints, or a larger one?).

现在，我的方法是先缝合两个2x1图像，然后将这两个图像缝合在一起.它与我们想要的接近，但是仍然不能接受.同样，问题可能是图像曾经是源"(而第二个图像是用矩阵进行变换以使其重叠的)，可能不会有点未对准，或者该图像上的角度很小，会影响整个结果

Right now, my approach is to first stitch two 2x1 images and then, stitch these two together. It's close from what we want, but still not acceptable. Also, the problem might be that the image used to be the "source" (while the second image is transform with the matrix to overlap that one) might not be a bit misaligned or there's a small angle on that image that affects the whole result.

任何帮助或建议，我们将不胜感激.特别是，任何允许使用OpenCV和SURF的解决方案(即使我并不完全反对其他库……也就是大多数项目都是以此为基础开发的.)

Any help or suggestion is appreciated. Specially any solution that would allow to use OpenCV and SURF (even if I'm not totally against other libraries... it's just that most of the project has been developed with that).

谢谢！

推荐答案

我发现使用 TurboReg 在图像配准开发过程中成为有用的比较工具.它是一个免费的 ImageJ 插件，并且具有许多不同的适配类型.

I found using TurboReg during image registration development to be a helpful comparison tool. It is a free ImageJ plugin, and has many different fitting types.

您是否看过新的OpenCV缝合示例: stitching.cpp 和 stitching_detailed.cpp ?

Have you taken a look at the new OpenCV stitching samples: stitching.cpp and stitching_detailed.cpp?

我忘了这是最先进的OpenCV，因为我在家中使用中继:)要访问这些新样本，您需要从SVN中检出OpenCV中继.像这样:

EDIT : I forgot this was cutting edge OpenCV because I'm using the trunk at home :) To get access to these new samples, you'll need to check out the OpenCV trunk from SVN like this:

svn co https://code.ros.org/svn/opencv/trunk/opencv opencv-trunk

不幸的是，您需要重新编译它，但是您应该能够使用新的拼接代码:)如果您以前从未从源代码构建过OpenCV，请

Unfortunately, you'll need to recompile it, but you should be able to use the new stitching code :) If you haven't built OpenCV from source before, here is a good little tutorial to get you started. I will mention that OpenCV has a lot more options that can be enabled/disabled than are mentioned in the tutorial, so you might want to use the cmake-gui to get a look at all of the options. You can apt-get it with this command:

> sudo apt-get install cmake-qt-gui

此外，如果您更关注质量，并且不介意性能降低，您可以考虑使用 Lucas-Kanade方法进行图像配准. 此处是一次讲座，此处是关于该主题的论文对您有帮助.

Also, if you're more concerned with quality, and you don't mind slower performance; you might consider using the Lucas-Kanade method for image registration. Here is a lecture, and here is a paper on the topic that might be helpful to you.

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