人工智能
计算机视觉
图像融合
小波
光学(聚焦)
稳健性(进化)
计算机科学
小波变换
像素
图像分辨率
景深
迭代重建
曲面重建
自动对焦
图像(数学)
曲面(拓扑)
数学
光学
物理
几何学
化学
基因
生物化学
作者
Hui Xie,Weibin Rong,Lining Sun
标识
DOI:10.1109/iros.2006.282641
摘要
Microscopy imaging can not achieve both high resolution and wide image space simultaneously. Autofocusing and 3-D surface reconstruction techniques are of fundamental importance to automated micromanipulation in providing high lever task understanding, task planning and real time control. In this paper, a new wavelet-based focus measure is developed, which provides significantly better depth resolution accuracy, and robustness than previous ones. A complex valued wavelet-based microscopic image fusion method and 3-D surface reconstruction scheme were proposed. Purpose of image fusion is to combine those multi-focus images into one single clear composite image with an extended depth-of-field. Combined 2-D position data of "in focus" pixels with a height map obtained from the proposed image fusion method, a 3-D surface reconstruction algorithm of microparts is developed. Experimental results validate the performances of the proposed image fusion and 3-D surface reconstruction methods
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