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Saliency Detection for Seismic Applications Using Multi-dimensional Spectral Projections and Directional Comparisons

Citation Author(s):
Muhammad Amir Shafiq, Zhiling Long, Tariq Alshawi, Ghassan AlRegib
Submitted by:
Muhammad Amir Shafiq
Last updated:
13 September 2017 - 12:20am
Document Type:
Presentation Slides
Document Year:
2017
Event:
Presenters:
Ghassan AlRegib
Paper Code:
ICIP1701
 

In this paper, we propose a novel approach for saliency detection for seismic applications using 3D-FFT local spectra and multi-dimensional plane projections. We develop a projection scheme by dividing a 3D-FFT local spectrum of a data volume into three distinct components, each depicting changes along a different dimension of the data. The saliency detection results obtained using each projected component are then combined to yield a saliency map. To accommodate the directional nature of seismic data, in this work, we modify the center-surround model, proven to be biologically plausible for visual attention, to incorporate directional comparisons around each voxel in a 3D volume. Experimental results on real seismic dataset from the F3 block in Netherlands offshore in the North Sea prove that the proposed algorithm is effective, efficient, and scalable. Furthermore, a subjective comparison of the results shows that it outperforms the state-of-the-art methods for saliency detection.

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