Image restoration is an effective way to improve the quality of images degraded by wave-front aberrations. If the wave-front aberration is too large, the performance of the image restoration will not be good. In this paper, the relationship between the performance of image restoration and the degree of wave-front aberrations is studied. A set of different wave-front aberrations is constructed by Zernike polynomials, and the corresponding PSF under white-light illumination is calculated. A set of blurred images is then obtained through convolution methods. Next we recover the images with the regularized Richardson-Lucy algorithm and use the RMS of the original image and the homologous deblurred image to evaluate the quality of restoration. Consequently, we determine the range of wave-front errors in which the recovered images are acceptable.