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FocusALL: Focal Stacking of Microscopic Images Using Modified Harris Corner Response Measure

机译:FocusALL:使用改进的哈里斯角响应测量法对显微图像进行焦距叠加

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摘要

Automated image analysis of microscopic images such as protein crystallization images and cellular images is one of the important research areas. If objects in a scene appear at different depths with respect to the camera's focal point, objects outside the depth of field usually appear blurred. Therefore, scientists capture a collection of images with different depths of field. Focal stacking is a technique of creating a single focused image from a stack of images collected with different depths of field. In this paper, we introduce a novel focal stacking technique, FocusALL, which is based on our modified Harris Corner Response Measure. We also propose enhanced FocusALL for application on images collected under high resolution and varying illumination. FocusALL resolves problems related to the assumption that in focus regions have high contrast and high intensity. Especially, FocusALL generates sharper boundaries around protein crystal regions and good in focus images for high resolution images in reasonable time. FocusALL outperforms other methods on protein crystallization images and performs comparably well on other datasets such as retinal epithelial images and simulated datasets.
机译:微观图像的自动图像分析(例如蛋白质结晶图像和细胞图像)是重要的研究领域之一。如果场景中的物体相对于相机焦点出现在不同的深度,则景深以外的物体通常会显得模糊。因此,科学家捕获了具有不同景深的图像集合。焦距堆叠是一种从使用不同景深收集的图像堆栈中创建单个聚焦图像的技术。在本文中,我们介绍了一种新颖的焦点堆叠技术FocusALL,它是基于经过改进的哈里斯角响应量度。我们还建议使用增强型FocusALL,以应用于在高分辨率和变化照明条件下收集的图像。 FocusALL解决了与以下假设有关的问题:在焦点区域具有高对比度和高强度。特别是,FocusALL会在蛋白质晶体区域周围产生更清晰的边界,并且在合理的时间内可以很好地聚焦于高分辨率图像。在蛋白质结晶图像上,FocusALL的性能优于其他方法,并且在其他数据集(例如视网膜上皮图像和模拟数据集)上表现相当出色。

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