A novel brain image enhancement method based on nonsubsampled contourlet transform

In this article, a novel brain image enhancement approach based on nonsubsampled contourlet transform (NSCT) is proposed. First, the image is decomposed into a low-frequency component and several high-frequency components by the NSCT; Second, the gamma correction is applied to deal with the low-frequency sub-band coefficients, and the adaptive threshold is used to remove the noise of the high-frequency sub-bands coefficients; Third, the inverse nonsubsampled contourlet transform is adopted to reconstruct the processed coefficients; Finally, the unsharp filter is used to enhance the reconstructed image. The experimental results demonstrate that the performance of the proposed method is superior to the state-of-the-art algorithms in terms of brain image enhancement.