改进各向异性导向滤波的明场显微图像清晰化方法

Bright-Field Microscopic Image Sharpening Method with Improved Anisotropy Guided Filtering

针对光学显微成像系统由于CCD采集、成像对焦精度等不利因素导致成像图像模糊的问题,提出一种改进各向异性导向滤波的反锐化掩模明场显微图像的清晰化方法。首先,通过改进自适应正则项的各向异性导向滤波消除图像噪声,同时强保留边缘细节信息;其次,利用各向同性的高斯滤波得到强平滑图像结构信息;然后,将细节强保留图像与结构强平滑图像相减,得到掩模图像;最后将输入图像与掩模图像融合,得到清晰的显微图像。该方法减少了传统反锐化掩模算法放大图像噪声导致图像细节特征辨识度降低的现象,在一定程度上降低了图像的模糊感,同时避免了滤波处理结果出现梯度反转和光晕伪影。在Mendeley data公开数据库的利什曼原虫寄生虫数据集实验结果中,所提方法的清晰度评价指标峰值信噪比、均方根误差和平均结构相似度的平均值分别为41.1430、0.000090和0.9905;而在PanNuKe公开数据库实验结果中,所提方法的3个指标平均值分别为28.8541、0.001939和0.9283。主客观的实验结果表明,所提方法能够减少噪声干扰和抑制细节“光晕”问题,同时能够更好地增强边缘细节信息。

To address the blurring of imaging images caused by unfavorable factors such as CCD acquisition and imaging focus depth in optical microscopic imaging systems,this study proposes a method for enhancing the clarity of bright-field microscopic images of unsharp masks by improving the anisotropy-guided filtering.First,the image noise is eliminated by improving the anisotropy-guided filtering of the adaptive regularization term while strongly retaining the edge detail information.Next,the isotropic Gaussian filtering is used to achieve strong smooth image structure information and the details are strongly preserved.The detail-preserving image is subtracted from the strongly-smoothed image to obtain the mask image.Finally,the input image is fused with the mask image to obtain a clear microscopic image.The proposed method overcomes the phenomenon that the traditional unsharp mask algorithm amplifies the image noise and reduces the recognition of image detail features.Furthermore,our method reduces the blurring of the image to a certain extent and avoids gradient inversion and halo artifacts in the filtering results.In the experimental results of the Leishmania parasite dataset on the Mendeley data public database,the average value of the sharpness evaluation indicators such as the peak signal-to-noise ratio,root mean square error,and average structural similarity is 41.1430,0.000090,and 0.9905,respectively.Meanwhile,in the experimental results on the PanNuKe public database,the average value of the abovementioned three indicators is 28.8541,0.001939,and 0.9283,respectively.Subjective and objective experimental results show that the proposed method can reduce noise interference and suppress detail“halo”problems as well as enhance edge detail information.