I am working in QGIS 2.18 with thermal image raster data, and I would like to isolate from the total pixels in the image those that form a group of values higher than the average of their closest environment.
The basic idea is to identify those groups of pixels with high values, hotspots, to convert them to points.
In short, use a thermal image to identify hot spots automatically.
I did as @Kazuhito did but the result is not very encouraging. The idea is to find a process to identify hot spots in a mosaic of thermal images taken with an RPA.
Problem that I have in many cases, that the mosaic is burned on one side, very high values, or that very high values of temperatures are grouped, which can be rocks, bare ground, etc ...
If I run the local algorithm minimun and maximun of SAGA I get many records.
Would there be some way to preprocess the image to obtain better results?