We’re using a Parrot Sequoia integrated with an Sensefly eBee.
This is a image stack (IR Band - Red color gun, Green Band - Green color gun, Red Band - Blue color gun). It does this in no matter the radiometric calibration option chosen in the index calculator tab.
Is it possible that flight line had bright sun spots? It looks like a sun spot affect. You could check your raw images to see if they have the bright spots.
I am experiencing a similar issue when stitching images from a slantrange 3p sensor. I also see striping that corresponds to the flight path, and in some images, I see the eliptical artifacts that spot along the path as well.
Using the reflectance maps would be the right thing to do in this case. The orthomosaics are color balanced that do not contain the reflectance values and when blended may lead to such artifacts.
To share the files you could use WeTransfer or a public Google Drive folder.
I’m not sure I have the same problem. Here is what I am seeing with individual reflectance maps. I see the striping intermittently, sometimes with certain bandwidths and not others…
This would happen either by not a satisfactory reconstruction or if the sunshine sensor is registering bad the sun irradiance. To take a look could you upload your project to our Cloud?
You could also share here the p4d, log file, and quality report so I could see the radiometric corrections that you have applied for are.
To upload the project, please follow the instructions that are given here.
I am also suspicious of the internal calibration. The data was collected with a slantrange 3p sensor. I will upload the data so that you can take a look.
As discussed I have take a closer look at the project.
The main issue here is the overlap which is not meeting the requirements for such reconstruction.
Because of this your point cloud has parts that are very noisy:
Reflectance Map is obtained from DSM. The DSM is generated from the _ filtered point cloud. The filtered point cloud is generated from the densified point cloud that is generated based on the Automatic Tie points _. That being said higher the quality of the Point Cloud then higher the quality of all the other outputs.
To obtain satisfactory results for this project you will have to clean the point cloud and re-run step 3.
To clean the point cloud, you can follow the instructions that are given here.
For future flights, please consider having a very high overlap; least 85% frontal overlap and at least 70% side overlap. Flying higher is also recommended since the images suffer from fewer perspective distortions.
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