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http://dx.doi.org/10.7582/GGE.2021.24.1.006

Evaluating Accuracy of Algorithms Providing Subsurface Properties Using Full-Reference Image Quality Assessment  

Choi, Seungpyo (Department of Convergence Study on the Ocean Science and Technology, Korea Maritime and Ocean University)
Jun, Hyunggu (Marine Active Fault Research Unit, Korea Institute of Ocean Science and Technology)
Shin, Sungryul (Department of Energy Resources Engineering, Korea Maritime and Ocean University)
Chung, Wookeen (Department of Energy Resources Engineering, Korea Maritime and Ocean University)
Publication Information
Geophysics and Geophysical Exploration / v.24, no.1, 2021 , pp. 6-19 More about this Journal
Abstract
Subsurface physical properties can be obtained and imaged by seismic exploration, and various algorithms have been developed for this purpose. In this regard, root mean square error (RMSE) has been widely used to quantitatively evaluate the accuracy of the developed algorithms. Although RMSE has the advantage of being numerically simple, it has limitations in assessing structural similarity. To supplement this, full-reference image quality assessment (FR-IQA) techniques, which reflect the human visual system, are being investigated. Therefore, we selected six FR-IQA techniques that could evaluate the obtained physical properties. In this paper, we used the full-waveform inversion, because the algorithm can provide the physical properties. The inversion results were applied to the six selected FR-IQA techniques using three benchmark models. Using salt models, it was confirmed that the inversion results were not satisfactory in some aspects, but the value of RMSE decreased. On the other hand, some FR-IQA techniques could definitely improve the evaluation.
Keywords
human visual system; full-reference image quality assessment; waveform inversion; accuracy evaluation;
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