如何检测图像中的光斑？

In short, you'll get a very poor estimate of size using your method. The edges of the blurred regions, no matter what threshold you pick, do not correspond to the edges of the inselbergs you want to measure. Instead, I suggest you follow the recipe below. I'm using DIPlib in Python for this (disclaimer: I'm an author). The Python bindings are a thin layer on the C++ library, it's fairly simple to translate the Python code below to C++ (it's just easier for me to develop it interactively in Python).

I downloaded the original height data from the link you provided (rather than the declivity). DIPlib can directly read floating-point valued TIFF files, so there is no need for any special conversion. I cropped a region similar to the one used by OP for this demo, but there is no reason to not apply the method to the whole tile.

import PyDIP as dip

height = dip.ImageRead('17S42_ZN.tif')
height.SetPixelSize(0.000278, 'rad')  # not really radian, but we don't have degrees
height = height[3049:3684, 2895:3513];

The code also sets the pixel size according to data in the TIFF file (using units of radian, because DIPlib doesn't do degrees).

Next, I apply the top-hat filter with a specific diameter (25 pixels). This isolates all peaks with a diameter of 25 pixels or less. Adjust this size according to what you think the maximum width an inselberg should be.

local_height = dip.Tophat(height, 25)

In effect, the result is a local height, the height above some baseline determined by the size of the filter.

Next, I apply a hysteresis threshold (double threshold). This yields a binary image, thresholded at 100m above the baseline, where the terrain goes above 200m above that baseline. That is, I decided that an inselberg should be at least 200m above the baseline, but cut each of them off at 100m. At this height we'll be measuring the size (area). Again, adjust the thresholds as you see fit.

inselbergs = dip.HysteresisThreshold(local_height, 100, 200)

Now all that is left is measuring the regions we found:

labels = dip.Label(inselbergs)
result = dip.MeasurementTool.Measure(labels, features=['Size', 'Center'])
print(result)

This outputs:

   |       Size |                  Center | 
-- | ---------- | ----------------------- | 
   |            |       dim0 |       dim1 | 
   |     (rad²) |      (rad) |      (rad) | 
-- | ---------- | ---------- | ---------- | 
 1 |  1.863e-05 |     0.1514 |    0.01798 | 
 2 |  4.220e-05 |     0.1376 |    0.02080 | 
 3 |  6.214e-05 |    0.09849 |    0.04429 | 
 4 |  6.492e-06 |     0.1282 |    0.04710 | 
 5 |  3.022e-05 |     0.1354 |    0.04925 | 
 6 |  4.274e-05 |     0.1510 |    0.05420 | 
 7 |  2.218e-05 |     0.1228 |    0.05802 | 
 8 |  1.932e-05 |     0.1420 |    0.05689 | 
 9 |  7.690e-05 |     0.1493 |    0.06960 | 
10 |  3.285e-05 |     0.1120 |    0.07089 | 
11 |  5.248e-05 |     0.1389 |    0.07851 | 
12 |  4.637e-05 |     0.1096 |    0.09016 | 
13 |  3.787e-05 |    0.07146 |     0.1012 | 
14 |  2.133e-05 |    0.09046 |    0.09908 | 
15 |  3.895e-05 |    0.08553 |     0.1064 | 
16 |  3.308e-05 |    0.09972 |     0.1143 | 
17 |  3.277e-05 |    0.05312 |     0.1174 | 
18 |  2.581e-05 |    0.07298 |     0.1167 | 
19 |  1.955e-05 |    0.04038 |     0.1304 | 
20 |  4.846e-05 |    0.03657 |     0.1448 | 

(Remember, where it says 'rad' it is really degrees.) An area in square degrees is a bit weird, but you can convert this to square meters since you know the location on the globe. It might in fact be easier to translate the pixel sizes to meters before the computations.

此处为“中心”指定的值是相对于左上角像素的，如果我们最初没有裁剪图块，则可以添加图块的坐标（可以从的相应标签中获得TIFF文件）：（-42.0，-17.0）。

在C ++中，代码应如下所示：

#include <diplib/simple_file_io.h>
#include <diplib/morphology.h>
#include <diplib/segmentation.h>
#include <diplib/regions.h>
#include <diplib/measurement.h>

//...

dip::Image height = dip::ImageRead("17S42_ZN.tif");
height.SetPixelSize(0.000278 * dip::Units::Radian());
height = height.At(dip::Range(3049, 3684), dip::Range(2895, 3513));

dip::Image local_height = dip::Tophat(height, 25);

dip::Image inselbergs = dip::HysteresisThreshold(local_height, 100, 200);

dip::Image labels = dip::Label(inselbergs);
dip::MeasurementTool measurementTool;
dip::Measurement result = measurementTool.Measure(labels, {}, {"Size", "Center"});
std::cout << result;