13 October 2016 Remote sensing image enhancement based on the combination of nonsubsampled shearlet transform and guided filtering
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Abstract
Aiming at the characteristics of remote sensing images with low-contrast, weak edge preservation, and poor resolution textual information, an image enhancement method that combines nonsubsampled shearlet transform (NSST) and guided filtering is presented. First, histogram equalization is applied to the remote sensing image. Second, the image is decomposed into a low frequency component and several high frequency components by NSST. Then, a linear stretch is adopted for the coefficients of the low-frequency component to improve the contrast of the original image; the threshold method is used to restrain the noise in the high-frequency components, then guided filtering is used for dealing with the high-frequency components, improving the detail information and edge-gradient retention ability. Finally, the final enhanced image is reconstructed by applying the inverse NSST to the processed low- and high-frequency components. The results show that the algorithm can significantly improve the visual impression of the image. Compared with the proposed algorithms in recent years, the average gradient and information entropy are significantly improved and the running time is shortened.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Duliang Lv, Duliang Lv, Zhenhong Jia, Zhenhong Jia, Jie Yang, Jie Yang, Nikola Kasabov, Nikola Kasabov, } "Remote sensing image enhancement based on the combination of nonsubsampled shearlet transform and guided filtering," Optical Engineering 55(10), 103104 (13 October 2016). https://doi.org/10.1117/1.OE.55.10.103104 . Submission:
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