Study On Restoration Method Of The Defocused Image

With the development of the computer technology, the operational precision and rate of the computer have made great progress; the computer is used in the field of image processing far and wide. The objective of the study is to integrate the traditional optical theory with the burgeoning method of the digital image processing, to improve the restoration precision of the defocused image and lower design criterion of the optical equipment.According to the character of the item, the paper study the restoration of the defocused letter image mainly, but theory and practice prove that the method and conclusion are also suitable to the restoration of the common defocused image and other circular-symmetry blur image. The paper improves the traditional method of defocused restoration and does work as follows:Firstly, the paper introduces the defocused model in the traditional method of defocused restoration: Gauss model and Pillbox model; infers the factual defocused transfer function; points out that though using model can simplify the problem, but the model can't reflect the factual defocused point spread function exactly, that results in unsatisfactory restoration of defocused image.Secondly, based on the optical knowledge such as edge spread function, line spread function point spread function and Abel inverse transform etc., the defocused point spread function can be assessed through knife-edge function curve, according to the circular symmetry of the defocused image. This method improves the estimating precision of the point spread function. Wiener filter is fabricated for recovering the defocused image based on the defocused point spread function. The impact of the noise to the restoration is reduced greatly by Wiener filter.At last, the simulation experiment and actual defocused restoration experiment proved that: the improved method can assess the defocused point spread function and defocused optical transfer function more exactly than the traditional method, can gain clear image with higher resolution and contrast.