A novel brain image enhancement method based on nonsubsampled contourlet transform. Issue 2 (13th December 2017)

• Record Type: Journal Article
• Authors: Li, Liangliang; Si, Yujuan; Jia, Zhenhong
• Is Part Of: International journal of imaging systems and technology. Volume 28:Issue 2(2018)
• Page Start: 124
• Page End: 131
• Publication Date: 2017-12-13
• Subjects: adaptive threshold -- gamma correction -- NSCT -- unsharp filter; Imaging systems -- Periodicals; Image processing -- Periodicals; 621.367
• DOI: 10.1002/ima.22264
• Languages: English
• ISSNs: 0899-9457

Abstract

Abstract: 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.