Remote Sensing Image Enhancement Based on Nonsubsampled Shearlet Transform and Local Laplacian Filter

被引:0
|
作者
Li, Liangliang [1 ]
Si, Yujuan [1 ,2 ]
机构
[1] Jilin Univ, Coll Commun Engn, Changchun, Jilin, Peoples R China
[2] Jilin Univ, Zhuhai Coll, Dept Elect Informat, Zhuhai, Peoples R China
关键词
remote sensing image; image enhancement; nonsubsampled shearlet transform; local laplacian filter; UNSHARP MASKING; CONTOURLET TRANSFORM; NSCT DOMAIN;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To improve contrast for remote sensing image without suffering from insufficient details, this paper proposes an enhancement method for different remote sensing images based on nonsubsampled shearlet transform (NSST) and local laplacian filter. The input image is first decomposed into low-frequency and high-frequency components. Then, the chosen local laplacian filter is used to process the low-frequency coefficient, and the adaptive threshold is used to suppress the noise included in the high-frequency coefficient. Finally, the NSST is inversed to obtain the enhanced image. Visual and quantitative analysis indicate the significance of the proposed image enhancement scheme, as compared to state of the art techniques.
引用
收藏
页码:415 / 418
页数:4
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