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Discussion and Conclusions

Today, angle gather construction is acomputational bottleneck in terms of computation, cache misses, and IO. Compressive sensing, which reconstructs a sub-sampled signal by a $ \ell_1$ inversion of the data transformed into a sparse basis function, offers a potential solution. I showed that the angle gather constructions meets the two criterion for compressive sensing: the data is highly compressible using multi-dimensional wavelets and reducing the data size dramatically reduces computational cost. The next step in this work is to apply an $ \ell_1$ solver to reconstruct a sub-sampled offset gather.