  The most efficient signal edge-preserving smoothing filters, e.g., for
denoising, are non-linear. Thus, their acceleration is challenging and is often
performed in practice by tuning filter parameters, such as by increasing the
width of the local smoothing neighborhood, resulting in more aggressive
smoothing of a single sweep at the cost of increased edge blurring. We propose
an alternative technology, accelerating the original filters without tuning, by
running them through a special conjugate gradient method, not affecting their
quality. The filter non-linearity is dealt with by careful freezing and
restarting. Our initial numerical experiments on toy one-dimensional signals
demonstrate 20x acceleration of the classical bilateral filter and 3-5x
acceleration of the recently developed guided filter.
