核医学图象是指采用特殊的探测装置通过在人体外探测体内放射性核素分布而形成的图象，医学上常用这种图象来反映器官组织的形态与变化，由于其信噪比明显低于其他医学图象（X-ray,CT及MRI），图象粗糙，分辨率低，因此核医学图象处理方法显得比其他医学图象更为重要，为了获得较好的图象处理结果，针对动态核医学图象的特点，提出了一种用于动态核医学图象处理的自适应增强算法，用该算法进行图象处理不仅可增强图象的对比度和提高图象的视觉效果，而且可较好地滤除图象噪声，处理后的核医学图象判读效果很好，实验证明，该方法对处理灰度较低，噪声干扰较大的动态核医学图象是一种行之有效的方法，而对静态核医学图象则要依据γ图象的统计特性，采用适当的处理方法。

Nuclear medical image reflects form and change of organ organizes, using special exploration device to explore human body's radioactive nuclide distribute outside the human body. As the SNR of Nuclear medical image is obviously lower than other medical image(X-ray, CT and MRI), the picture of nuclear medical image is coarse and the resolving power is low, the processing method of nuclear medical image is obvious much more important than other medical images. In accordance with the characteristic of dynamic nuclear medical image, the self- adaptive enhancing and smoothing algorithm has been proposed, which is used for removing the noise of the nuclear medical image, enhancing the contrast of the nuclear medical image and improving the visual effect of nuclear medical image. After doing that, the reading effect of the nuclear medical image is much better. This method that the paper probe into is a kind of effectual method that is suitable for processing the relatively low gray level, the bigger noise interferes of the dynamic nuclear medicine image. However, the static nuclear medicine image should adopt the proper treatment method according to the statistics characteristics ofγpicture.