Edge detection using multiplication imaging conditions

This paper presents a new algorithm to generate edge detection images using a migrated image. The key idea is that discontinuity response are comprised of all dip angle ranges and thus after F-K filtering, they can exist in both images with negative-only and positive-only dips. However, reflection responses can only exist in either image with negative-only dips or image with positive-only dips. Applying multiplication imaging condition (MIC) to two images with opposite dips can generate an edge detection image. This method can be easily extended to 3D cases. More specifically, two strategies are proposed. The first one involves applying a 3D F-K filter to calculate four components with different dip and azimuth angles, then multiplying the decomposed four components to generate the final edge detection image. The other one consists of splitting the 3D data volume into 2D sections and then applying the 2D methodology to generate the edge detection image. Both synthetic and real data tests will be employed in 2D and 3D to demonstrate the validity of edge detection using MIC.