  Ultrasound 3D compounding is important for volumetric reconstruction, but as
of yet there is no consensus on best practices for compounding. Ultrasound
images depend on probe direction and the path sound waves pass through, so when
multiple intersecting B-scans of the same spot from different perspectives
yield different pixel values, there is not a single, ideal representation for
compounding (i.e. combining) the overlapping pixel values. Current popular
methods inevitably suppress or altogether leave out bright or dark regions that
are useful, and potentially introduce new artifacts. In this work, we establish
a new algorithm to compound the overlapping pixels from different view points
in ultrasound. We uniquely leverage Laplacian and Gaussian Pyramids to preserve
the maximum boundary contrast without overemphasizing noise and speckle. We
evaluate our algorithm by comparing ours with previous algorithms, and we show
that our approach not only preserves both light and dark details, but also
somewhat suppresses artifacts, rather than amplifying them.
