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IN THIS ARTICLE
Why radiometric correction?
What is radiometric correction?
How does PIX4Dfields perform radiometric correction?
For which cameras is radiometric correction performed?
Why do I need to specify the weather condition?
Why do I have holes in my orthomosaic?
How do I create reflection target images?
What’s the difference between PIX4Dfields and PIX4Dmapper regarding radiometry?
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Radiometric correction is required to be able to compare multispectral imagery taken at different points in time under different weather conditions, and to compute reliable index values.
The pixel values from the images depend on the lighting conditions and the camera sensor settings, among other variables, which usually change between flights. The correction solves that problem by compensating for external variables in order to estimate a physical property of the field. This is the reflectance factor.
The reflectance factor or more specifically, the hemispherical-directional reflectance factor, is a quantitative measure of the light reflection by an object which is illuminated by direct and indirect sunlight, like the crop. Because it does not depend on external variables, it should not change between flights unless there is a physical change in the crop.
In technical terms, radiometric correction refers to the process of computing an estimation of the at-object reflectance factor from images, by taking into consideration the scene illumination and sensor properties.
In the context of agriculture, it is the process of eliminating the effect of variable external factors, like weather conditions and camera sensor, to have a more precise indirect measurement of the physical properties of the crop.
This process is implemented in PIX4Dfields by an algorithm that corrects each pixel value based on a physical model of the image acquisition process, in particular, a model of light reaching the sensor. Many factors are involved in this process including but not limited to:
- Sensor settings: shutter speed, ISO, and aperture.
- Sensor properties: light transmission in the optics, sensing and digitisation in the chip.
- Scene conditions: incoming sunlight, camera location, and orientation.
PIX4Dfields performs radiometric corrections in a way that is very similar to PIX4Dmapper, which is explained in: Radiometric Correction in PIX4Dmapper.
PIX4Dfields performs different types of radiometric correction, depending on the availability of the following sources of information:
Image EXIF tags. PIX4Dfields scans the image EXIF tags, where most of the information required by the radiometric correction can be found.
Sunshine sensor. The use of a sunshine sensor improves the overall correction results by including more information about the illumination on the field (sun irradiance and, when supported by the hardware, sun angle). For supported camera models, this information is stored in the image EXIF tags and automatically detected by PIX4Dfields.
Reflectance targets. The use of a radiometric calibration target enables PIX4Dfields to calibrate and correct the images to reflectance according to a measurement given by the reflectance target. When using reflectance targets, the images must be imported for processing, like regular images, in order to be used for radiometric correction.
Thermal profile. The Parrot Sequoia+ camera creates a sequoia_therm.dat thermal profile file containing information that is used for radiometric correction. This file must be stored in the same folder as the images and is automatically taken into account.
Weather condition during capture. When required, PIX4Dfields will prompt the user for this information. It is therefore important to observe and save the weather condition during which a dataset was acquired.
The input images are radiometrically corrected individually before they are composed into the orthomosaic.
Currently, the following cameras are supported for radiometric correction in PIX4Dfields:
- Parrot Sequoia and Sequoia+.
- Micasense RedEdge, RedEdge-M, RedEdge-P, RedEdge-MX, Altum and Altum-PT.
- Sentera 6x and Sentera 6x Thermal.
- DJI P4 multispectral and Mavic 3 multispectral:
- These cameras are not fully radiometrically calibrated. Only a relative calibration is done by the manufacturer: All bands are calibrated against the standard NIR band. Therefore the cameras will not provide reflectance factors, but only relative values that are proportional to reflectance.
- A reflectance target is required to obtain reflectance factors. Without such a target, only indices that are self-normalizing produce meaningful results, i.e. indices that don't depend on the absolute value. Examples of such indices are NDVI, NDRE, VARI, SIPI2, LCI, BNDVI, and GNDVI. Not self-normalizing are TGI and MCARI.
- The orientation of the sunshine sensor is not known. Therefore the sun angle cannot be accounted for and only the correction type "Sun Irradiance" can be applied. Hence, weather condition is not required when processing.
- La Quinta DB2-Vision.
- Sentera NDRE/NDVI: Note that this camera does not provide a sun sensor, therefore the output is proportional to at-sensor radiance and a reflectance target is required to obtain reflectance factors.
- SenseFly modified Canon S110 NIR/RE: Note that this camera does not provide a sun sensor, therefore the output is proportional to at-sensor radiance and a reflectance target is required to obtain reflectance factors.
- Other modified cameras that provide the required radiometric information: See the camera requirements article for more information.
Weather and sun are significant factors that influence multispectral imagery. Cloud cover and solar position should be accounted for in order to minimize the effect of measurement errors caused by changes in ambient light. PIX4Dfields allows users to specify cloud cover with either overcast or clear sky options. In addition, if the camera is equipped with a sunshine sensor a sun angle correction will be performed under any weather conditions.
If certain pixels cannot be radiometrically corrected, they are marked internally, and not displayed (i.e. they are transparent). Such pixels appear as holes in the orthomosaic or index images.
Pixels cannot be radiometrically corrected if they are over or underexposed. This happens most often for highly reflective objects, such as cars or roofs.
The use of a radiometric calibration target enables PIX4Dfields to calibrate and correct the images to reflectance according to the values given by the reflectance target. Therefore, if the camera is not calibrated to allow a targetless workflow, the use of reflectance target images generally improves the accuracy of the radiometric correction.
PIX4Dfields supports the following reflectance targets:
- Airinov Aircalib
- MicaSense Calibrated Reflectance Panel
How to create good images of reflectance targets is described here: Radiometric calibration targets
In principle, PIX4Dfields uses the same radiometric correction as PIX4Dmapper. However, there are a few slight differences in its usage:
- In PIX4Dmapper, the correction type can be chosen by the user. For ease of use, PIX4Dfields does not let the user choose, but automatically determines the best possible correction type from the data, taking into account the weather condition if applicable. Unlike PIX4Dmapper, PIX4Dfields can also do sun angle correction for overcast conditions. The correction type that was used can be found in the report.
- PIX4Dfields uses a different, faster and less accurate way than PIX4Dmapper to compute the camera position and orientation and to stitch the images. Since that information is used in the radiometric correction, the reflectance values computed by PIX4Dfields can be slightly different to the ones by PIX4Dmapper due to minor differences in the computed camera orientation.
Register for a free 15 days trial to test radiometric correction in PIX4Dfields.