Enhancing Small Satellite Optical Imaging Performance Under Resolution Limitations in Diffraction, Motion, and Noise

Improving spatial resolution is essential for enhancing imaging results. However, optical imaging faces key constraints that affect image quality and resolution. This study analyzes the spatial and temporal coherence properties of light sources and demonstrates that resolution can be improved by limiting diffraction and using an appropriate lens. Additionally, relative motion between the camera and the vibrating object introduces motion blur, reducing measurement accuracy. To address this, a low-frequency vibration measurement method based on the motion blur mechanism is proposed. Motion blur is influenced by the camera shutter time and the amplitude, frequency, and direction of vibration. A mathematical model was developed to measure vibrations accurately based on motion blur. Results indicated that increasing the vibration amplitude from 10 to 30 μm reduced the modulation transfer function (MTF) at the Nyquist frequency by 17% while increasing the frequency from 1 to 40 Hz led to a 19% reduction in MTF. Sub-pixel displacement accuracy was evaluated using the digital image correlation (DIC) algorithm, but increased noise introduced systematic errors and position-dependent standard deviations, reducing registration accuracy. To mitigate noise, a median filter was applied to preprocess vibration-blurred images, improving contrast and reducing noise interference. Numerical simulations showed that for images with 2% Gaussian noise, mean absolute error (MAE) decreased from 1.09 to 0.82 pixels, while the RMSE and standard deviation errors decreased by 3.17 and 3.16 pixels, respectively.