An efficient method for computing local cross-correlations of multi-dimensional signals
نویسنده
چکیده
Consider two multi-dimensional digital signals, each with Ns samples. For some number of lags Nl Ns, the cost of computing a single cross-correlation of these two signals is proportional to Ns ×Nl. By exploiting several properties of Gaussian windows, we can compute Ns local cross-correlations, again with computational cost proportional to Ns×Nl. Here, local means the cross-correlation of signals after applying a Gaussian window centered on a single sample. Computational cost is independent of the size of the window.
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