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Blind correction of human lymphocyte images by optimal thresholding in UWT domain

机译：通过UWT域中的最佳阈值对人淋巴细胞图像进行盲校正

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Epidemiological studies have shown that the presence of chromosome damage or instability in human lymphocytes create the Micro Nucleuses (MNs) not incorporated into one of the daughter nuclei. Recently, the Image Flow Cytometer (IFC) was pointed out in order to acquire the image of the human lymphocytes, and to detect the MNs. The alterations introduced by the image acquisition system of the IFC causes errors in the automatic recognition, Therefore, proper methods were pointed out to correct them. The recurrent alterations are bad exposure, out of focus, motion blur, and Gaussian noise. In order to more increase the number of images correctly processed to detect and count the MNs, in the paper the new and optimized method able to perform the blind correction of the image affected by Gaussian noise is proposed. The method is based on the Un-decimated discrete Wavelet Transform (UWT). By taking into account the characteristics of the human lymphocyte images, the optimal value of threshold is evaluated with the aim to improve the quality of corrected image. Experimental tests are performed to compare the proposed correction method with the ones already available in the recent literature.
机译：流行病学研究表明，人类淋巴细胞中染色体损伤或不稳定性的存在会导致微核（MN）未被整合到子核之一中。最近，指出了图像流式细胞仪（IFC）以获取人淋巴细胞的图像并检测MN。 IFC图像采集系统引入的变更会导致自动识别中出现错误，因此，指出了纠正它们的正确方法。经常发生的变化是曝光不良，聚焦不清，运动模糊和高斯噪声。为了更多地增加对MN进行检测和计数的正确处理图像的数量，提出了一种能够对受高斯噪声影响的图像进行盲校正的新型优化方法。该方法基于未抽取的离散小波变换（UWT）。通过考虑人淋巴细胞图像的特征，评估阈值的最佳值，以提高校正图像的质量。进行了实验测试，以将所提出的校正方法与最近文献中已有的校正方法进行比较。

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