Improved Split Bregman Method for Fluorescence Microscopic Image Restoration
Abstract: 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.
文章引用: 张长春 , 王瑜 , 肖洪兵 (2016) 改进的分裂Bregman方法荧光显微图像复原。 建模与仿真， 5， 81-88. doi: 10.12677/MOS.2016.53011
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