One Complex Wavelet Algorithm Based on Image Deconvolution

In this paper, a new method PRECGDT-CWT is advanced, using the standard DT-CWT filters of the (13-19) taps near orthogonal filters at level 1 together with the 14-tap Q-shift filters at levels not less than 2. We chose ten iterations of the conjugate gradient algorithm used with the preconditioned system search direction starting from a ward estimate. We also compare the results with alternative deconvolution algorithms. The method of PRECGDT-CWT performed better than all the other methods tested and better than the published results on similar deconvolution experiments. In summary, complex wavelets appear to provide a useful Bayesian image model that is both powerful and requires relatively little computation.