改进的分裂Bregman方法荧光显微图像复原

Abstract

荧光显微图像复原有着很多重要的应用，例如，天文成像，电子显微镜成像，单光子发射计算机断层成像术和正电子发射断层成像技术等等。传统基于全变差的分裂Bregman算法能够很好地保护图像边缘和纹理信息，但在图像的平滑区域会产生严重的阶梯效应，针对这一问题，本文提出了一种复原算法，主要考虑两点，一是采用全变差(Total Variation, TV)正则化模型，可以很好地复原模糊图像。二是引入权函数，对TV进行加权抑制阶梯效应，同时保护了图像的纹理信息。通过对参数的合理选择，获得最佳的复原效果，在模拟图像和真实荧光显微图像的实验结果验证了该算法的有效性和可行性。 Fluorescence microscopic image restoration has many very important applications such as astro-nomical imaging, electronic microscopy, single particle emission computed tomography (SPECT) and positron emission tomography (PET). Traditional total variation imaging restoration based on split Bregman algorithm can preserve sharp edges and save the image texture. Serious staircase effect phenomena, however, is generally accompanied. Therefore an improved image restoration algorithm is proposed based on split Bregman in this paper, which is mainly considered two aspects. One is that the total variation regularization model is used, which is an effective tool to recover blurred images. The other is that the weight function of the total variation is involved, which can not only suppress the staircase effect, but also preserve the image texture information. By ap-propriately choosing the reasonable parameters, the better restoration results can be obtained. The experimental results on synthetic images and real fluorescence microscopic images show the effectiveness and feasibility of the proposed algorithm.