Interpolate 2D waves with non-uniform X,Y scalings NOT defined on the edges

I have data that represent values of a function F (X,Y).

X and Y are 1D waves that are neither linear not log scaled but monotonously increasing.

X and Y waves have different number of points , but constitute a grid.

I would like to interpolate the 2D wave to be able to estimate F at values between the grid points.

Browsing Igor Help, it seems that

would do it but this considers that the 1Dwave values correspond to the edges of the "pixels", according to Igor Help:

/W={xWave, yWave}

	Provides the scaling waves for XYWaves interpolation. Both waves must be monotonic and must have 

	one more point than the corresponding dimension in srcWave. The waves contain values corresponding 

	to the edges of data points in srcWave, so that the X value at the first data point is equal to 

	(xWave[0]+xWave[1])/2.

/S={x0,dx,xn,y0,dy,yn }	

	Calculates a bilinear interpolation of a subset of the source data. Here x0  is the starting point

	 in the X-direction, dx  is the sampling increment, xn  is the end point in the X-direction and 

	 the corresponding values for the Y-direction. If you set x0  equal to xn  the operation will 

	 compute the triangulation but not the interpolation.	

Is there another way to do a 2D interp from a non-uniform grid ?

I would like to avoid having to compute the 1D waves at the edges, do the 2D interp, then compute the values of the new 1Dwaves corresponding to the centers of the new pixels, not the edges...