[英]OpenCV Image Stitching - using ExposureCompensator and MultiabandBlender class
I am working a panoramic stitching project and I am trying to implement M. Brown and D. Lowe's Automatic Panoramic Image Stitching using Invariant Features by tweaking and adapting it to my needs.我正在做一个全景拼接项目,我正在尝试通过调整和适应我的需求来实现 M. Brown 和 D. Lowe 的使用不变特征的自动全景图像拼接。 I understand the OpenCV stitching method in stitcher class is based on this.
我了解拼接器类中的 OpenCV 拼接方法基于此。
I am stuck at the gain compensation and multi-band blending part.我被困在增益补偿和多频段混合部分。 While I understand the theory behind it fairly well, I am shaky on the implementation.
虽然我相当了解它背后的理论,但我对实现却很不稳定。
OpenCV has classes for both, ExposureCompensator and MultibandBlender but I am struggling to put them to use in code. OpenCV 有针对ExposureCompensator和MultibandBlender 的类,但我正在努力将它们用于代码中。
Has anyone sucessfully used any of these classes ?有没有人成功使用过这些课程? Are there any good examples ?
有什么好的例子吗?
While I was googling, I came across当我在谷歌搜索时,我遇到了
This tries to explain roughly how to use ExposureCompesator but does not explain what the inputs are.这试图粗略地解释如何使用 ExposureCompesator 但没有解释输入是什么。 Specifically, the inputs for feed method are
vector<Point>
corners and Vector<Mat>
masks.具体来说,feed 方法的输入是
vector<Point>
角和Vector<Mat>
掩码。
a) What are these corners ? a) 这些角是什么? Are these the top left corners of the individual images in the final panorama ?
这些是最终全景图中单个图像的左上角吗? or something else ?
还是别的什么?
b) What are the masks ? b) 面具是什么? How should I create them ?
我应该如何创建它们?
This tries to explain how to use the blender class but again misses the input definitions.这试图解释如何使用搅拌机类,但再次错过了输入定义。 What are the corners and masks ?
什么是角落和面具?
This is my stitched panorama, I am trying to compensate the exposure differences and blend it.这是我拼接的全景图,我正在尝试补偿曝光差异并将其融合。
Have a look into the official tutorial under the section Stitching detailed (python opencv >4.0.1)
.在
Stitching detailed (python opencv >4.0.1)
部分下查看官方教程。 There you have a detailed implementation within both C++ and Python where also compensation and blending is included!在那里你有 C++ 和 Python 的详细实现,其中还包括补偿和混合!
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