  We propose and experimentally demonstrate an efficient image decomposition in
the Laguerre-Gaussian (LG) domain. By developing an advanced computing method,
the sampling points are much fewer than those in the existing methods, which
can significantly improve the calculation efficiency. The beam waist, azimuthal
and radial truncation orders of the LG modes are optimized depending on the
image information to be restored. In the experiment, we decompose an image by
using about 30000 LG modes and realize a high-fidelity reconstruction.
Furthermore, we show image noise reduction through LG domain filtering. Our
results open a door for LG-mode based image processing.
