Study on the Evaluation Model of Image Definition
At present, the usual image definition evaluation methods are poor in focusing precision and have a lot of calculations. In view of these problems, the paper analyzed the factors affecting an image quality evaluation, and proposed two evaluation models based on an image contrast change rate and an autocorrelation function. These methods avoided efficiently the phenomenon of partial peaks of focusing-function curves for noise disturbing. The stimulant test proves that the focusing curve of the evaluation model in the paper has many advantages, such as good focusing performance, strong antijamming ability, good real time and so on.
G. J. Chen et al., "Study on the Evaluation Model of Image Definition", Applied Mechanics and Materials, Vols. 20-23, pp. 636-640, 2010