graphics - Why does a heavy background slow LocatorPane from updating, even if only the locators are Dynamic?

I'm having some trouble getting a dynamic plot to operate efficiently, and I think I've tracked down at least part of the problem to some pretty weird behaviour on the part of LocatorPane.

Take two different image backgrounds, which can be quite similar except for their size on disk:

image1 = ContourPlot[x^2-y^2, {x, -1, 1}, {y, -1, 1}, ImageSize -> 250];

image2 = ContourPlot[x^2-y^2, {x, -1, 1}, {y, -1, 1}, ImageSize -> 250, PlotPoints -> 200];

where the ByteCount of image2 is, in this case, about twenty times bigger than that of image1, and now use these images as the background for a LocatorPane:

point = {0.4, 0};
Row[{

  LocatorPane[
   Dynamic[point],
   image2
   ],
  Dynamic[point]
  }]

which produces something like this

enter image description here

As you can see, the version with the heavier background is a huge lot more sluggish than the lighter one (though this is much more evident if you run it yourself). Why is this? Both occurrences of point are inside a Dynamic command but the background is not, so I don't really see a reason for the background of the pane to be re-loaded every time the locators are changed. More importantly, how can this be avoided? I have a byte-heavy background which I would like to only calculate once and then display without it slowing me down.

I should also note that raster-based solutions will most likely prove unsatisfactory, particularly because I want to deploy a fair bit of information in the tooltips associated with the background contours.

Comments

plotting - Plot 4D data with color as 4th dimension

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plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1....

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