###### 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 factors of the slanted-edge method and proposes an improved slanted-edge method to calculate the MTF testing method of remote sensing cameras, which is applied to the MTF testing of remote sensing cameras. Since the traditional algorithm can only be applied in the small angle situation, this paper proposes a new method of slanted-edge method test calculation based on the optimal oversampling rate (OSR) adaptive model of the slanted edge and uses simulation experiments to verify the reliability of the algorithm model through the deviation of the slanted-edge angle calculation and MTF measurement, and the results show that the algorithm improves the accuracy of the MTF measurement compared with the ISO-cos and OMINI-sine methods. Then, the effects of the slanted-edge angle, image region of interest (ROI), as well as image contrast and signal-to-noise ratio (SNR) on the accuracy of the MTF calculation by the slanted-edge method were quantitatively analyzed as the constraints of the slanted-edge method test. Based on the laboratory target experiment, the algorithm flow and various influencing factors obtained in the simulation stage are verified, and the experimental results are more consistent with the various test results obtained in the simulation stage. Consequently, the slanted-edge method introduced in this paper is applicable for future remote sensing camera MTF testing. This approach offers a valuable reference for on-orbit focusing, satellite operational condition monitoring, lifespan estimation, and image restoration. remote sensing camera; MTF; slanted-edge method; accuracy analysis; influencing factors Article  
Analysis of the Slanted-Edge Measurement Method for the Modulation Transfer Function of Remote Sensing Cameras  
[PERSON]. MTF detection methods vary depending on the target used, including the three-bar method [4], slanted-edge method [5], slit method [6], and Siemens Star method [7; 8]. Currently, laboratory testing of camera MTF predominantly employs the three-bar and slanted-edge methods, as other methods face limitations due to challenges in target processing, extended testing durations, and poor repeatability, leading to less frequent application. The slanted-edge method, a primary technique for remote sensing camera MTF detection [9], involves rotating a slanted-edge target at a specific angle relative to the detector's rows or columns. This rotation projects and rearranges the pixels of the slanted-edge image based on a predefined rule [10], thereby enhancing the image's sampling rate and mitigating under-sampling issues. Recognized as an indirect approach for measuring the MTF, the slanted-edge method has been successfully implemented in the in-orbit MTF measurement of satellites such as IKONOS [11; 12], Orbview [13], GF-4 [14], and Quickbird [15]. The International Organization of Standards endorses this method as well (ISO12233:2023) [16], which involves analyzing a camera-captured slanted-edge target image to determine the edge spread function (ESF) [17], differentiating the ESF to acquire the line spread function (LSF), and then applying Fourier transform on the LSF and taking the modes to compute the MTF [18; 19]. Offering a comprehensive evaluation at various spatial frequencies in a single instance and characterized by rapid detection, the slanted-edge method has garnered significant scholarly interest [20]. The accuracy of the slanted-edge method hinges on precise estimation of the image edge angle, as this directly impacts the MTF calculation results. [PERSON] et al.