Basic applicable conditions and upper limits for improving spatial resolution of image restoration and super-resolution reconstruction were researched theoretically by using discrete-to-discrete imaging model. The quantitative indices of applicable conditions based on image processing were given. Experiments on restoration and SRR were carried out by simulating different sampling frequencies and SNR low-resolution images, and the results were analyzed in detail. The perfect consistence was obtained between the theory and experiment.