Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain

被引:11
|
作者
Li, Liangliang [1 ]
Si, Yujuan [1 ,2 ]
Jia, Zhenhong [3 ]
机构
[1] Jilin Univ, Coll Commun Engn, Changchun 130012, Jilin, Peoples R China
[2] Jilin Univ, Zhuhai Coll, Dept Elect Informat, Zhuhai 519041, Peoples R China
[3] Xinjiang Univ, Coll Informat Sci & Engn, Urumqi 830046, Peoples R China
来源
AIP ADVANCES | 2018年 / 8卷 / 03期
关键词
CONTOURLET TRANSFORM; NSCT;
D O I
10.1063/1.4998400
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied to process the low-frequency sub-band coefficients, and the improved adaptive threshold is adopted to suppress the noise of the high-frequency sub-bands coefficients. Third, the processed coefficients are reconstructed with the inverse NSST. Finally, the unsharp filter is used to enhance the details of the reconstructed image. Experimental results on various microscopy mineral images demonstrated that the proposed approach has a better enhancement effect in terms of objective metric and subjective metric. (c) 2018 Author(s).
引用
收藏
页数:9
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