The real time image quality influences the performances of scene matching extensively, but there is no general metric for its quality assessment. Furthermore, different matching algorithms are of diverse sensitivity to various image features. Therefore, the study on image quality assessment (IQA) should be carried out according to the style of algorithms. Firstly, applications of IQA were described. Then, the assessment criteria were analyzed from two aspects: imaging quality and target saliency metric. An evaluation system, which includes signal to noise ratio (SNR), blur metric, local saliency metric (LSM) and global saliency metric (GSM), was presented. Experiments show that these criteria are consistent with the probability of the matching algorithm.