Optimal filtering with linear canonical transformations allows smaller
mean-square errors in restoring signals degraded by linear time- or s
pace-variant distortions and non-stationary noise. This reduction in e
rror comes at no additional computational cost. This is made possible
by the additional flexibility that comes with the three free parameter
s of linear canonical transformations, as opposed to the fractional Fo
urier transform which has only one free parameter, and the ordinary Fo
urier transform which has none. Application of the method to severely
degraded images is shown to be significantly superior to filtering in
fractional Fourier domains in certain cases.