在矩阵中查找更高数字的区域-Findingregionsofhighernumbersinamatrix

I am working on a project to detect certain objects in an aerial image, and as part of this I am trying to utilize elevation data for the image. I am working with Digital Elevation Models (DEMs), basically a matrix of elevation values. When I am trying to detect trees, for example, I want to search for tree-shaped regions that are higher than their surrounding terrain. Here is an example of a tree in a DEM heatmap:

我正在研究一个项目来检测航拍图像中的某些物体,作为其中的一部分,我正在尝试利用图像的高程数据。我正在使用数字高程模型(DEM),基本上是高程值矩阵。例如,当我试图检测树木时,我想搜索高于周围地形的树形区域。以下是DEM热图中树的示例:

https://i.stack.imgur.com/pIvlv.png

I want to be able to find small regions like that that are higher than their surroundings.

我希望能够找到比周围环境更高的小区域。

I am using OpenCV and GDAL for my actual image processing. Do either of those already contain techniques for what I'm trying to accomplish? If not, can you point me in the right direction? Some ideas I've had are going through each pixel and calculating the rate of change in relation to it's surrounding pixels, which would hopefully mean that pixels with high rates change/steep slopes would signify an edge of a raised area.

我正在使用OpenCV和GDAL进行实际的图像处理。这些中的任何一个已经包含了我想要完成的技术吗?如果没有,你能指出我正确的方向吗?我所拥有的一些想法是通过每个像素并计算与其周围像素相关的变化率,这有望意味着具有高速率变化/陡峭斜率的像素将表示凸起区域的边缘。

Note that the elevations will change from image to image, and this needs to work with any elevation. So the ground might be around 10 meters in one image but 20 meters in another.

请注意,高程将从图像更改为图像,这需要适用于任何高程。所以地面可能在一幅图像中大约10米,而在另一幅图像中大约20米。

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