Abstract: The nonsubsampled contourlet transform is a fully shift invariant, multi-scale, and multi-direction expansion that has better directional frequency localization and a fast implementation. We proposed a novel image denoising method by incorporating the nonsubsampled contourlet transform. The fully shift invariant property and the high directional sensitivity of the nonsubsampled contourlet transform make the new method a very good choice for image denoising.Firstly, the image was decomposed in different subbands of frequency and orientation responses using the nonsubsampled contourlet transform. Then the multi-scale thresholds were computed according to noise distribution, and used to shrink the nonsubsampled contourlet coefficients. Finally, the modified nonsubsampled contourlet coefficients were transformed back into the original domain to get the denoised image. Simulation results show that the method can obtain higher peak-signal-to-noise ratio, compared with other recent image denoising methods, such as wavelet denoising and contourlet denoising.

Key words: Image denoising, Nonsubsampled contourlet transform, Multi scale threshold, Gibbs