Abstract
A new method of objectively assessing image quality is presented. This method deals with imaging system Modulation Transfer Function (MTF) and Signal to Noise Ratio (SNR), which are very important for image quality assessment based on matching accuracy requirements in the digital photogrammetric processing. Firstly, the main metrics affecting image quality is theoretically analyzed and mathematically modeled. Subsequently, variations of matching accuracy with MTF and SNR metrics are analyzed, and mathematical model between them is developed based on Back-Propagation Neural Network (BPNN). Finally, the model is verified using real aerial images. The model can be used to predict the effects of MTF and SNR metrics on the matching accuracy, then assess image quality and system design performance according to special matching accuracy requirements.
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