A Novel Remote Sensing Image Enhancement Method Using Unsharp Masking in NSST Domain

2018 ◽  
Vol 46 (9) ◽  
pp. 1445-1455 ◽  
Author(s):  
Liangliang Li ◽  
Yujuan Si
2016 ◽  
Vol 39 (2) ◽  
pp. 183-193 ◽  
Author(s):  
Lu Liu ◽  
Zhenhong Jia ◽  
Jie Yang ◽  
Nikola Kasabov

The intelligibility of an image can be influenced by the pseudo-Gibbs phenomenon, a small dynamic range, low-contrast, blurred edge and noise pollution that occurs in the process of image enhancement. A new remote sensing image enhancement method using mean filter and unsharp masking methods based on non-subsampled contourlet transform (NSCT) in the scope for greyscale images is proposed in this paper. First, the initial image is decomposed into the NSCT domain with a low-frequency sub-band and several high-frequency sub-bands. Secondly, linear transformation is adopted for the coefficients of the low-frequency sub-band. The mean filter is used for the coefficients of the first high-frequency sub-band. Then, all sub-bands were reconstructed into spatial domains using the inverse transformation of NSCT. Finally, unsharp masking was used to enhance the details of the reconstructed image. The experimental results show that the proposed method is superior to other methods in improving image definition, image contrast and enhancing image edges.


2011 ◽  
Vol 12 (6) ◽  
pp. 453-460 ◽  
Author(s):  
Shan-long Lu ◽  
Le-jun Zou ◽  
Xiao-hua Shen ◽  
Wen-yuan Wu ◽  
Wei Zhang

2013 ◽  
Vol 13 (1) ◽  
pp. 153-158 ◽  
Author(s):  
Qian Li ◽  
Zhenhong Jia ◽  
Xizhong Qin . ◽  
Yingjie Hu . ◽  
Jie Yang .

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