光学(聚焦)
插值(计算机图形学)
计算机视觉
人工智能
图像复原
图像(数学)
对象(语法)
迭代重建
计算机科学
序列(生物学)
图像质量
数学
图像处理
模式识别(心理学)
算法
光学
遗传学
物理
生物
作者
K. Pradeep,Ambasamudram Narayanan Rajagopalan
标识
DOI:10.1109/tip.2007.899188
摘要
The shape-from-focus (SFF) method uses a sequence of frames to estimate the structure of a 3-D object. Its accuracy depends on the step size by which the translational table is moved while capturing the images. Existing SFF algorithms use an ad hoc interpolation strategy to account for the error due to the finite step size. We propose an improved SFF method that uses relative defocus blur derived from actual image data to arrive at the final estimates of the structure of the object. A space-variant image restoration scheme is also proposed to obtain a focused image of the 3-D object. The reconstructed 3-D structure as well as the quality of the restored image are superior for the proposed method in comparison to traditional SFF.
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