Bio-inspired orientation analysis for seismic image

In this paper, we propose a novel method of orientation analysis for seismic image. Unlike conventional methods of orientation estimation with a context window, our method is inspired by the neural mechanism of visual perception in the biological brain. In the brain, the primary visual cortex contains orientation columns, which is composed of an array of simple cells as orientation detectors. A log-Gabor filter with a specific orientation and scale configuration simulates the neuronal mechanism of the simple cell, while an array of such orientation detectors simulates the neuronal responses of the orientation columns. The resulting orientation is derived at the pixel level of the input seismic image: the neuronal response of each simple cell competes with other cells in the same orientation column for the same pixel, and the winning neuron with maximum response defines the perceived orientation. We applied the proposed method to seismic interpretation to analyze the orientation patterns, and it also can be used as a general image orientation analysis tool.