Graz, Austria • October 5, 2023
Vexcel Imaging is presenting a white paper authored by Marc Muick, Project Lead and Application Engineer at Vexcel Imaging, offering an in-depth comparative analysis of panchromatic and Bayer pattern sensors. This analysis provides valuable insight into the merits and limitations of these technologies, shedding light on their impact on resolution, image quality, and efficiency in aerial survey applications.
In aerial imaging, the selection of sensor technology is crucial in determining the quality and efficiency of aerial data collection. Two prevalent sensor categories in this domain are panchromatic and Bayer pattern sensors.
We conducted an intensive examination using a panchromatic CCD sensor and a Bayer pattern-based CCD sensor, featuring the same pixel pitch and utilizing the same lens setup.
The primary goal was to assess the resolution differences between these two sensor types. As we explored the correlation between Ground Sampling Distance (GSD) and resolution, it became evident that panchromatic sensors excel in capturing finer details at the same GSD. Additionally, we observed notable susceptibilities of Bayer pattern sensors to artifacts such as moiré and maze patterns, which can pose challenges to image quality across various applications. Furthermore, we delved into the influence of the color of the captured object—or target—on the resulting loss of resolution.
In aerial survey applications, the ability to fully resolve details is crucial for photogrammetric workflows and derived products. While panchromatic-based sensors remain the premium standard for highest image and data quality, a more cost-effective and spatially efficient Bayer pattern sensor proves beneficial in fundamental scenarios marked e.g. by spatial constraints, such as camera systems characterized by oblique cones.
Understanding the strengths and limitations of each sensor type allows for informed decisions when selecting aerial camera systems for specific applications.
Panchromatic versus Bayer pattern sensors.
Discover the following key findings of this analysis in the figure below by moving the arrow up and down: