计算机科学
度量(数据仓库)
结构光
相(物质)
光学
图像质量
质量(理念)
高动态范围
航程(航空)
人工智能
融合
计算机视觉
算法
动态范围
材料科学
图像(数学)
数据挖掘
物理
语言学
哲学
复合材料
量子力学
作者
Zhiyong Pan,Kai Zhong,Zhongwei Li,baohui zhang
出处
期刊:Optics Express
[The Optical Society]
日期:2022-04-19
卷期号:30 (9): 14600-14600
被引量:13
摘要
Using structured light to measure the 3D shape of a high dynamic range (HDR) surface has been always a challenging problem, and fusion of multi-group images with different exposures is recognized as an effective solution. It tends to select the phase with unsaturated and maximum gray intensity as the final phase, which has two problems: 1) the selection criteria are too simple to fully evaluate the phase quality, and 2) it is affected by the image noise, camera's nonlinear response, local reflection and other factors and the phase with the best quality among the initial phases may also have an error. Aiming to solve these issues, this paper presents a hybrid-quality-guided phase fusion (HPF) model. In this model, a hybrid-quality measure is first proposed to evaluate the phase quality more comprehensively. Then, all initial phases are weighted and fused under the guidance of the hybrid-quality measure to obtain a more accurate phase as the final one. Through this model, a more complete and accurate 3D shape of the HDR surface can be reconstructed, and its validity has been verified by several experiments.
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