In this article, we introduce three key metrics that are essential for describing the resolution of a drone camera. To clarify these concepts, we'll use examples from the cameras of the drones we know best—specifically, the Elios 1 and Elios 2.
## Pixel Resolution
The **pixel resolution** of an image refers to the total number of pixels that make up the image. It's typically expressed as the number of columns and rows, like 1920 x 1080, or as the total number of pixels, such as 2.1 MP (1920 x 1080 equals approximately 2.07 million pixels).
Here's a quick breakdown of the pixel resolutions for Elios 1 and Elios 2:
| Feature | Elios 1 Pixel Resolution | Elios 2 Pixel Resolution |
|---------------|--------------------------|--------------------------|
| FHD Video | 1920 x 1080 | 1920 x 1080 |
| | 2.1 MP | 2.1 MP |
| 4K Video | N/A | 3840 x 2160 |
| | | 8.3 MP |
| Photo | N/A | 4000 x 3000 |
| | | 12 MP |
While the pixel resolution gives us an idea of the image size, it doesn't tell us much about how large an object appears in the image or the level of detail we can observe. For that, we need other metrics like the ground sampling distance and the spatial resolution.
| Metric | Application |
|------------------------------|---------------------------------|
| Pixel Resolution | Data sharing, storage, display |
| Ground Sampling Distance (GSD)| Measurements, photogrammetry |
| Spatial Resolution | Smallest detectable object |
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## Ground Sampling Distance (GSD)
The **ground sampling distance (GSD)**, measured in mm/px, is the distance between the centers of two adjacent pixels on the object being imaged. A GSD of 1mm/px means each pixel corresponds to 1 mm in the real world. A lower GSD implies that objects will appear larger and finer details will be more visible in the image.
Unlike pixel resolution, GSD is influenced by the distance between the camera and the subject. As the camera gets closer to the object, the GSD improves (decreases). With a fisheye lens, GSD also varies depending on the object's position within the image. Objects in the center of the image have a smaller GSD (appear larger), while those at the edges or corners have a higher GSD (appear smaller).
[Image: Elios 2 GSD at 50 cm]
[Image: Elios 2 GSD at 30 cm]
*This figure demonstrates how GSD changes across the image when the Elios 2 is positioned directly in front of a flat vertical wall. It was generated by automatically measuring the size of a regular grid pattern on the wall.*
GSD is critical for photogrammetry and making precise measurements from images. However, it doesn't fully capture the camera's ability to detect and characterize objects or defects.
Consider two images captured under similar conditions by the same camera. Both images might have the same pixel resolution and GSD, but one could suffer from poor lighting, leading to increased ISO values or longer exposure times. High ISO introduces image noise, while long exposure times can result in motion blur if the camera moves. These factors reduce image quality and the ability to distinguish fine details.
[Image: Weld overview side-by-side]
[Image: Weld detail side-by-side]
*The top two images were taken by Elios 2 at the same distance and have identical pixel resolution and GSD. However, the image on the right is affected by motion blur, making it less detailed than the left image, where the drone was steady.*
---
## Spatial Resolution
The **spatial resolution**, or angular resolution, measures the smallest details that can be seen in an image. Unlike theoretical GSD, spatial resolution considers additional factors like blur, image noise, contrast, and post-processing techniques such as compression, denoising, and edge sharpening. Therefore, spatial resolution is the best metric for evaluating the camera's ability to detect and characterize objects.
Spatial resolution is commonly expressed in "line pairs per millimeter" (lp/mm). This unit describes the spatial frequency of alternating black and white line patterns.
[Image: Line pair explanation]
*Left: Pattern with a frequency of 2.5 lp/mm. Right: 5 lp/mm*
A spatial resolution of 2 lp/mm means the camera can distinguish a pattern with two cycles per millimeter (two black and two white lines). Patterns with higher frequencies will appear gray due to blending of the black and white lines, meaning they are unresolved.
[Image: Elios 2 USAF 1951 resolution test]
*Snapshot of an image taken by Elios 2 (4K video) at 300 mm from a USAF 1951 resolution chart. The smallest resolved element is element 1, group 1 (indicated by the green arrow). Element 2 (below) shows significant contrast loss, making it impossible to distinguish individual lines.*
Spatial resolution is generally better in the center of the image than at the edges, where lens quality is often lower. Additionally, spatial resolution is an isotropic property, meaning vertical and horizontal line patterns may not be resolved equally.
Spatial resolution also depends on the camera's focus distance and depth of field. For Elios 2, the highest spatial resolution is achieved when the object is 15 to 30 cm away from the camera. If the object is closer, it will appear larger in the image (lower GSD), but it will likely be out of focus and blurry, reducing spatial resolution.
To achieve the best spatial resolution, it's crucial to know the minimum distance allowed by the drone's focal length and maintain that distance during data capture. Elios 2 helps pilots fly at the optimal distance with features like distance lock and Cockpit (the Control Station application), which display the drone-to-object distance and resulting GSD (in mm/px). Spatial resolution is indicated through a color-coded system, as shown below:
| Distance | Color | Meaning |
|-----------------|-------------|-------------------------------------------|
| > 40 cm | White | Closer approach increases spatial resolution |
| 30 to 40 cm | Green | High spatial resolution and sharp image |
| 20 to 30 cm | Orange | Highest spatial resolution but blurry image |
| < 20 cm | Red | Very blurry image; spatial resolution drops |
Note that smaller screens can mask image blurriness because the image is scaled down to match the screen resolution. With Elios 2, you might be tempted to fly at 15-20 cm without realizing the blurriness. However, your recorded 4K footage will look sharper if you stay at 30 cm.
Beyond maintaining the right distance, other factors improve spatial resolution and overall image quality:
- Ample lighting to keep ISO low and exposure times short
- Stable flight to avoid motion blur
- Clean camera lenses—fingerprints can cause glare and blur
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## Beyond Resolution
While spatial resolution is vital for assessing image quality and detecting objects during inspections, other elements are equally important:
- Lighting techniques
- Colors (contrast, white balance)
- Ability to view objects from multiple angles
- Display screen quality
These aspects extend beyond mere resolution and must be addressed holistically by the entire Unmanned Aerial System (UAS). The compact size of Elios 2 and its collision-resistant design allow it to access hard-to-reach areas and observe objects from various angles. Its advanced lighting system enhances the perception of 3D details, making it easier to spot cracks, holes, or irregularities. These features significantly contribute to Elios 2's ability to detect and characterize objects of interest.
With practice, you'll refine your piloting skills and focus more on data collection than navigation. Keeping the principles discussed here in mind will dramatically improve your footage's quality.
Different industries have varying image quality requirements. If you've experimented with comparing tools or have feedback about Elios 2's image quality, feel free to reach out!
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I hope this clarifies the concepts of pixel resolution, GSD, and spatial resolution. Let me know if you have any further questions!
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