A wire is coiled into a helix whose surface is a cylinder. I show that a filter on the 1-D space of the wire mimics a 2-D filter on the cylindrical surface. Thus 2-D convolution can be done with a 1-D convolution program. Likewise, I show some curious examples of 2-D recursive filtering (also called 2-D deconvolution or 2-D polynomial division). In 2-D as in 1-D, the computational advantage of recursive filters is the speed with which they propagate information over long distances. We can estimate 2-D prediction-error filters (PEFs), that are assured of being stable for 2-D recursion. Such 2-D and 3-D recursions vastly speed the solution of a wide class of geophysical estimation problems. Simple tasks that are vastly speeded are (1) estimating missing values on a multidimensional cartesian mesh, and (2) distributing irregularly positioned data on a regular mesh.