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首页> 外文期刊>Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic >Adaptive optics retinal image registration from scale-invariant feature transform
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Adaptive optics retinal image registration from scale-invariant feature transform

机译:尺度不变特征变换的自适应光学视网膜图像配准

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摘要

With the use of adaptive optics(AO), high-resolution microscopic imaging of the living human retina in the single cell level has been achieved. In an AO retinal imaging system, with a small field size (about 1°, 300 μm) the motion of the eye severely affects the stabilization of the real-time video images results in significant distortions of the retina images. Scale-invariant feature transform (SIFT) algorithm is applied to automatically abstract corner points with subpixel resolution and match the points in two frames. With the matched corner points, we estimate and remove the motions of 20 frames of photoreceptor cells and capillary blood vessels, respectively. The maximal translational motion is about 30 and 44 pixels in the 20 frames whose size is 416 × 416 pixels. More general motions can be considered by the SIFT algorithm, but only simple translational motion can be considered by cross-correlation algorithm.
机译:通过使用自适应光学系统(AO),可以在单个细胞水平上实现对人类视网膜的高分辨率显微成像。在AO视网膜成像系统中,视野较小(约1°,300μm),眼睛的运动会严重影响实时视频图像的稳定性,从而导致视网膜图像严重失真。尺度不变特征变换(SIFT)算法用于自动提取具有亚像素分辨率的角点,并在两个帧中匹配这些点。通过匹配的拐角点,我们分别估计和删除20帧感光细胞和毛细血管的运动。在20个帧中,最大平移运动约为30和44像素,尺寸为416×416像素。 SIFT算法可以考虑更一般的运动,而互相关算法只能考虑简单的平移运动。

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