Preprocessing (white balance, temperature, exposure, noise reduction, sharpening…)

PIX4Dmapper PIX4Dmapper Questions/Troubleshooting
1

Hello,
I understand why original images are needed for processing, but i read this in the following article:
“After the flight, the RAW image files were converted to high quality jpegs (536) and some sharpening and noise reduction was added using the NIX software suite before importing the images into Pix4D software.”, from:
http://blog.pix4d.com/post/102602042516/aerial-imagery-project-for-land-and-building
So my question is:
Is it ok to preprocess images (RAW, jpeg, tif) using (ex. Using Adobe Camera RAW, Lightroom or Topaz DeNoise,…), of course with “pixel to pixel” operations, such as white balance, temperature, exposure, noise reduction, sharpening…? Does it creates problems, or it can help Pix4D to create better results?
Regards

1 Like
2

I am interested in this issue as well. For change detection and research purposes, we need to have very good radiometric calibration to compare fields through time.

In addition to your questions, I have several for Pix4D regarding the radiometric calibration option in Step 3.

  • Does the calibration image need to be taken on the ground prior to flying? We have an entire season’s worth of surveys where we use calibration targets, but only have images of them from 70-100m above ground level.
  • We have a greyscale “target” that is actually composed of 3 ceramic tiles painted white, grey, and black. Which tile should we use to calibrate against? Each tile is 30inches apart to prevent mixed pixels.
  • We will use a spectrometer, sprectroradiometer, or radiometer (I do not know which is most suitable) to obtain reflectance measurements. How can I convert these to albedo?

Thanks for the great work!

3

Hi all,

@Mario:

In general, it is not recommended to preprocess the images, especially if the preprocessing changes the geomerty of the images.
In some extreme cases (see https://support.pix4d.com/hc/en-us/articles/203341269-How-to-Process-Images-with-Big-Color-Variance) we recommend some preprocessing as a last effort to solve processing problems.

If you are working with multispectral images, then you should do some preprocessing based on the instructions of the following article: 

https://support.pix4d.com/hc/en-us/articles/204894705-Camera-Requirements-For-Precision-Agriculture

@Jacob: 

  • The calibration target image does need to be taken on the ground. If you have a big calibration target that is visible from the air and covers many pixels, then it is fine to take the image during the flight. If this is not possible, then we recommend to take the calibration target image before or after flying (under the same weather/lightening conditions) 
  • If you can take good images (not overexposed or underexposed) of your targets, it does not matter what is their color. We would recommend you to work with the grey tiles as it is easier to take images that are not overexposed or underexposed.
  • For more information about how to work with a spectroradiometer, see the post: https://community.pix4d.com/t/4749-Radiometric-Calibration-Target 

Best regards,

 

4

I put a data set of underexposed photos thru a auto-enhance photo software. This gave me a visually better looking output from PIX4D and I got suprised to see better stats in the qualityreport compared with the raw photo process.

 

5

Hi Goran,

Thank you for sharing this information with us.

Is it possible to receive from you a comparison of your projects/results before and after the pre-processing the images?

It’d be nice to see the difference you obtained.

Thank you in advance

6

Absolute. Se attached documents. Id like to hear your thoughts about it.

“Raw” photo quality report: https://drive.google.com/file/d/1_9taGHj2epdQTxJahPeAxuB-i_EpZdjx/view?usp=sharing 

Auto-enhanced photo quality report: https://drive.google.com/file/d/1UMltoX4ZsOlvoQAJJZ77wnmof9lE_4hd/view?usp=sharing 

 

7

Hi Goran,

Thank you so much for this datasets. It’s amazing how the parameters had changed.
Camera optimization decreased from 3.31% to 0.21%, 1 % more images were calibrated and median of matches per calibrated images increased from 9907.23 to 15749.7!

Very informative is also this comparison:
Quality Report, Figure 5  - Computed image positions with links between matched images.
Raw data

Data after pre-processing (levels, light, contrast)

Good job! :slight_smile:

Regards,