Improved Split Bregman Method for Fluorescence Microscopic Image Restoration

Fluorescence microscopic image restoration has many very important applications such as astronomical 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 appropriately 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.