为了对模糊图象进行高保真度的复原，研究了讨论了一种模糊图象的反扩散恢复算法；该算法首先以图象模糊的尺度为准，在比较为逐次递推算法和传统的单击算法的基础上，给出了它们的适应范围，进而提出了“搜寻－单击”算法，它用逐步逼近方式来探定未知的模糊尺度，然后以尺可能小的累积误差完成反扩散计算，从而实现了模糊图象恢复的盲处理，最后，采用自然模糊与人工模糊的图偈对恢复算法进行了验证，包括算法对模糊尺度的灵敏度算法的有效应用范围，以及纹理结构或景深偏差变化的模糊图象经恢复处理后的效果比较等，试验结果表明对数字图象作为SOS反扩散恢复处理可产生常规光学摄影技术所不可能取得的场景清晰度。

Images may be blurred due to diffusion. This paper investigates the inverse diffusion algorithms for restoration of such images. The conventional One Shoot(OS) algorithm and the Successive Recursion (SR) algorithm are analysed, their performance are compared, and the limits to their validity scopes are revealed and formulated in terms of the blur scales; all these lead to propose a novel "Search and One Shoot" (SOS) algorithm, where the unknown blur scale of a diffused image is detected in a successive approximation manner and the inverse diffusion computing is accomplished in One Shoot with an as small accumulative error as possible. Then, both natural and artificial blurred images are used for tests on the restoration algorithms, including their sensitivity to blur scales of images, their validity scopes , and the effects of SOS algorithm applied to blurred images of incoherent textural structure or scene depth, etc.The experimental results provides evidence that the digital image restoration using inverse diffusion technique can make images of high clarity in scene depth that is beyond the capability of common optical` photographic techniques.