Inter-scale correlation and threshold combination denoising model of nonsubsampled contourlet

Correlation denoising could distinguish noisy and signal coefficients by the correlation degree and thus retain more right edge. But there is a strict requirement to unerring locations. The nonsubsampled contourlet (NSCT) is a shift-invariant directional multiresolution image representation and overcomes the disadvantage of wavelet, the nonoptimal basis for one-dimensional singularity. For the shift-invariance, it could not only preserve more edge details than contourlet but also satisfy the above requirement of correlation denosing. Thus, to combine threshold denoising, we present a novel inter-scale correlation and threshold combination denosing model of NSCT (ISCTC-NSCT). The simulation results have shown that the performance of the above method is superior both in signal to noise ratio (SNR) and edge preservation.