Forward Looking Infrared (FLIR) image quality is of great importance for the detection and tracking algorithms to accurately locate the targets. In the field of Automatic Target Recognition (ATR), present researches on FLIR image quality are mainly related to the content of the scene, while ignoring the influence of imaging degradations on image quality. Through analysis of the cause of noise and blur, and combination with the former simulation methods, a new method was established for noise and blur simulation in images acquired by high-performance FLIR equipment. This method has been applied to analyze the effect of different degrees of noise and blur on image quality, and it can be concluded that noise has adverse effect on image quality, while blur is not always deleterious. Based on this conclusion, denoising method has been adopted in the preprocessing of FLIR image. Comparison among experimental results reveals that denoising method can improve the matching probability more effectively than sharpening method.