Basic Description: Balance uses a least squares approach to minimize differences in between tile edges by simultaneously adjusting the means of all tiles. This goal of this operation is similar to the Warp Operation, but Balance often produces much better results.

Technical Details: This operation is based on the method described by J.G.B. Haigh in “Automatic grid balancing in geophysical survey”, Computer Applications and Quantitative Methods in Archaeology, 1991, pages 191-196. The operation first scans all selected tiles and then associates data values from different tiles that are within a specified distance (essentially, this pairs data samples that are adjacent to each other on the edges of tiles). The difference between theses paired values are treated as observations in a least squares adjustment. The parameters of the least squares model are the means of the selected tiles. The least squares model will try to simultaneously minimize the difference between all paired values (i.e. force the difference to be as close to zero as possible) by adjusting the tile means. As with all least squares models, extreme observations (in this case, the paired-value differences) will have a larger than expected effect on the parameter estimates. For this reason, the algorithm excludes paired-value differences that are more than three standard deviations from the mean of all differences. However, it is still good practice to Despike or Clip the selected tiles first. Also note that the least squares model is under-determined since the combined mean of all the tiles can be any value and not affect the differences. The Balance Operation overcomes this deficiency by forcing the resulting combined mean to remain unchanged.

Instructions: Choose a selection method and make your selection on the survey, then run the operation stack. There are no parameters to set.