Reading your post I'm not exactly sure what you're looking for. I'm not a "resampling" expert, but 3 options come to mind:
1) You could use the SeaDAS
mapimg command to transform your L2 data to an array of any size you like and use a projection that gives you equidistant spacing. There will be no gaps or interpolation between pixels because the projection code will just repeat pixel values to fill the resultant image.
2) You could use the SeaDAS
l2bin command, setting the resolution to 0.5, 1, 2, 4, 9, or 36 kilometer resolution. Here the resultant image could have missing pixels due to unfilled bins, or some pixels could be the average of multiple pixels that all fell within the same bin.
3) You could do a straight resampling of the data using a preexisting IDL function (I'm not sure the one you're looking for exists, but maybe read the help for procedures like
triangulate,
congrid,
rebin, etc.), or write your own code, or I seem to remember Matlab having a good resampling function.
I know this may not help much but if you can explain exactly what you're trying to do maybe someone can give more help.