Experimental results show that benchmarked algorithms are highly sensitive to tested challenging conditions, which result in an average performance drop of 0. 17 in terms of precision and a performance drop of 0. 28 in recall under severe conditions.
In this paper, we propose a novel approach for saliency detection for seismic applications using 3D-FFT local spectra and multi-dimensional plane projections.
In this paper, we propose a saliency-based attribute, SalSi, to detect salt dome bodies within seismic volumes.
Based on the study, we then develop an algorithm that estimates a pixel-wise uncertainty map that reflects our confidence in the associated computational saliency map by relating a pixel's saliency to the saliency of its neighbors.
In this paper, we propose a workflow based on SalSi for the detection and delineation of geological structures such as salt domes.