4D Hyperspectral Photoacoustic Data Restoration with Reliability Analysis
4D Hyperspectral Photoacoustic Data Restoration with Reliability Analysis
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DOI：
10.1109/cvpr46437.2021.00457
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发表时间：
2021-06
期刊：
影响因子：
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通讯作者：
Weihang Liao;Art Subpa-Asa;Yinqiang Zheng;Imari Sato
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文献类型：
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作者：
Weihang Liao;Art Subpa-Asa;Yinqiang Zheng;Imari Sato
高光谱光声（HSPA）光谱是一种新兴的双模态成像技术，能够显示三维体积内部的波长相关吸收分布。然而，HSPA设备必须在空间域和频谱域中穷尽地扫描对象;并且所获取的数据往往遭受复杂的噪声。这种耗时的扫描过程和噪声严重影响了HSPA的可用性。因此，从不完整和有噪声的观测中检查4D HSPA数据恢复的可行性是至关重要的。在这项工作中，我们提出了一个数据的可靠性分析的深度和频谱域。在此分析的基础上，我们探讨了固有的数据相关性，并开发了一种恢复算法来恢复4D HSPA立方体。通过对真实的数据的实验，验证了该方法取得了令人满意的恢复效果。
Hyperspectral photoacoustic (HSPA) spectroscopy is an emerging bi-modal imaging technology that is able to show the wavelength-dependent absorption distribution of the interior of a 3D volume. However, HSPA devices have to scan an object exhaustively in the spatial and spectral domains; and the acquired data tend to suffer from complex noise. This time-consuming scanning process and noise severely affects the usability of HSPA. It is therefore critical to examine the feasibility of 4D HSPA data restoration from an in-complete and noisy observation. In this work, we present a data reliability analysis for the depth and spectral domain. On the basis of this analysis, we explore the inherent data correlations and develop a restoration algorithm to recover 4D HSPA cubes. Experiments on real data verify that the proposed method achieves satisfactory restoration results.