Analysis of the Slanted-Edge Measurement Method for the Modulation Transfer Function of Remote Sensing Cameras
Jian Yu,
Yu Zhang,
Biao Qi
et al.
Abstract:The modulation transfer function (MTF) serves as a crucial technical index for assessing the imaging quality of remote sensing cameras, which is integral throughout their entire operational cycle. Currently, the MTF evaluation of remote sensing cameras primarily relies on the slanted-edge method. The factors influencing the slanted-edge method’s effectiveness are broadly classified into two categories: algorithmic factors and image factors. This paper innovatively comprehensively analyzes the influencing facto… Show more
“…Our method involved using a slanted edge test object ( Figure 2 a) positioned at a constant distance from a uniform background panel, creating a distinct difference in depth values between the test object and the panel. The slanted edge is commonly used to determine modulation transfer function (MTF) in optical systems and allows us to determine a system’s ’sharpness’ performance at all spatial frequencies in one go [ 22 ]. Images of this arrangement were captured with the back panel set at various distances 10 mm, 50 mm, and 160 mm—as illustrated in Figure 3 .…”
This paper presents a fully automated experimental setup tailored for evaluating the effectiveness of augmented and virtual reality technologies in healthcare settings for regulatory purposes, with a focus on the characterization of depth sensors. The setup is constructed as a modular benchtop platform that enables quantitative analysis of depth cameras essential for extended reality technologies in a controlled environment. We detail a design concept and considerations for an experimental configuration aimed at simulating realistic scenarios for head-mounted displays. The system includes an observation platform equipped with a three-degree-of-freedom motorized system and a test object stage. To accurately replicate real-world scenarios, we utilized an array of sensors, including commonly available range-sensing cameras and commercial augmented reality headsets, notably the Intel RealSense L515 LiDAR camera, integrated into the motion control system. The paper elaborates on the system architecture and the automated data collection process. We discuss several evaluation studies performed with this setup, examining factors such as spatial resolution, Z-accuracy, and pixel-to-pixel correlation. These studies provide valuable insights into the precision and reliability of these technologies in simulated healthcare environments.
“…Our method involved using a slanted edge test object ( Figure 2 a) positioned at a constant distance from a uniform background panel, creating a distinct difference in depth values between the test object and the panel. The slanted edge is commonly used to determine modulation transfer function (MTF) in optical systems and allows us to determine a system’s ’sharpness’ performance at all spatial frequencies in one go [ 22 ]. Images of this arrangement were captured with the back panel set at various distances 10 mm, 50 mm, and 160 mm—as illustrated in Figure 3 .…”
This paper presents a fully automated experimental setup tailored for evaluating the effectiveness of augmented and virtual reality technologies in healthcare settings for regulatory purposes, with a focus on the characterization of depth sensors. The setup is constructed as a modular benchtop platform that enables quantitative analysis of depth cameras essential for extended reality technologies in a controlled environment. We detail a design concept and considerations for an experimental configuration aimed at simulating realistic scenarios for head-mounted displays. The system includes an observation platform equipped with a three-degree-of-freedom motorized system and a test object stage. To accurately replicate real-world scenarios, we utilized an array of sensors, including commonly available range-sensing cameras and commercial augmented reality headsets, notably the Intel RealSense L515 LiDAR camera, integrated into the motion control system. The paper elaborates on the system architecture and the automated data collection process. We discuss several evaluation studies performed with this setup, examining factors such as spatial resolution, Z-accuracy, and pixel-to-pixel correlation. These studies provide valuable insights into the precision and reliability of these technologies in simulated healthcare environments.
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