Contourlet域數(shù)據(jù)分析表明，信號的變換域系數(shù)在尺度間相關(guān)性高，而白噪聲則呈弱相關(guān)
或不相關(guān)。通過相關(guān)性強(qiáng)弱區(qū)分噪聲與信號系數(shù)，并結(jié)合閩值函數(shù)，提出了基于Contourlet變換尺度間相關(guān)的圖像去噪新算法。實(shí)驗(yàn)結(jié)果表明，新方法去噪后的圖像比小波相關(guān)去噪算法的PSNR值更高，視覺效果更好，尤其適用于紋理輪廓豐富的圖像去噪。

Analyses of Contourlet coeficients indicate that inter-scale contourlet coeficients with
respect to signals are highly correlated while the correlations associated with white noise are less or even do not exist．According to the property,an image denoising algorithm based on inter-scale corelations of Contourlet COOficients iS proposed combined with threshold functions．Experimental results show that the proposed method outperforms the coresponding wavelet method in term s of both peak-signal—to-noise(PSNR)and visual quality,and it is especially adequate to the images with much texture．