Jia Man, Xu Jingmei, Yang Ruoxi, Li Zongan, Zhang Ling, Wu Ye
School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, 210046, China.
College of Microelectronics and Communication Engineering, Chongqing University, Chongqing, 400044, China.
Heliyon. 2023 Sep 16;9(9):e20191. doi: 10.1016/j.heliyon.2023.e20191. eCollection 2023 Sep.
Fluorescence images enhancement is important as it can provide more information for medical diagnosis. In this work, we design three simple yet useful filters based on the combinations of mathematical functions, which are proved to be effective in strengthening the images acquired from the fluorescence microscope. Using these filters, detailed objects can be found in the dark sections of the fluorescence images. In addition, these filters can be used to enhance the low-light image, which provide satisfactory visual information and marginal profile for the blurred objects in the image. Moreover, these filters have been used to enhance the image with high degradation by the Gaussian noise, where clear edge profile can be extracted. Finally, we have shown that these filters can be utilized for the image compression. Compression ratio can be obtained to be 0.9688. This study shows the making of the filters with dual functions for the image enhancement and the image compression. Our designed filters are showing the potentials in the field of biomedical imaging and pattern identification.
荧光图像增强很重要，因为它可以为医学诊断提供更多信息。在这项工作中，我们基于数学函数的组合设计了三种简单但有用的滤波器，事实证明这些滤波器在增强从荧光显微镜获取的图像方面是有效的。使用这些滤波器，可以在荧光图像的暗区中找到细节物体。此外，这些滤波器可用于增强低光图像，为图像中模糊的物体提供令人满意的视觉信息和边缘轮廓。而且，这些滤波器已被用于增强受高斯噪声高度退化的图像，在这种情况下可以提取清晰的边缘轮廓。最后，我们已经表明这些滤波器可用于图像压缩。压缩比可达0.9688。这项研究展示了具有图像增强和图像压缩双重功能的滤波器的制作。我们设计的滤波器在生物医学成像和模式识别领域显示出潜力。
