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Enhancement of hyperspectral remote sensing images based on improved fuzzy contrast in nonsubsampled shearlet transform domain

  • Liangliang Li
  • Yujuan SiEmail author
Article
  • 16 Downloads

Abstract

In order to deal with the pseudo-Gibbs phenomenon in the process of hyperspectral remote sensing image enhancement, a novel image enhancement method based on nonsubsampled shearlet transform (NSST) is proposed in this paper. The main motivation of this study is to adjust the coefficient of remote sensing image enhancement as a pattern recognition task. Firstly, the input image is decomposed into a low-frequency component and some high-frequency components by NSST decomposition; Secondly, the guided filter is applied to process the low-frequency component to improve the contrast, and the improved fuzzy contrast is used to suppress the noise of the high-frequency components; Thirdly, the processed coefficients of low-frequency and high-frequency are reconstructed by inverse nonsubsampled shearlet transform (INSST), and the final enhanced image is obtained. The experimental results demonstrate that the proposed approach has obvious advantages in terms of objective data and subjective vision.

Keywords

Hyperspectral remote sensing image NSST Guided filter Fuzzy contrast 

Notes

Acknowledgments

We thank all the volunteers and colleagues provided helpful comments on previous versions of the manuscript. The experimental measurements and data collection were carried out by Liangliang Li and Yujuan Si. The manuscript was written by Liangliang Li with assistance of Yujuan Si. We would like to thank Prof. Yujuan Si for her contributions in proofreading of the paper. This work was supported by the Key Scientific and Technological Research Project of Jilin Province under Grant Nos. 20150204039GX and 20170414017GH; the Natural Science Foundation of Guangdong Province under Grant No. 2016A030313658; the Innovation and Strengthening School Project (provincial key platform and major scientific research project) supported by Guangdong Government under Grant No. 2015KTSCX175; the Premier-Discipline Enhancement Scheme Supported by Zhuhai Government under Grant No. 2015YXXK02-2; the Premier Key-Discipline Enhancement Scheme Supported by Guangdong Government Funds under Grant No. 2016GDYSZDXK036.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Communication EngineeringJilin UniversityChangchunChina
  2. 2.Department of Electronic InformationZhuhai College of Jilin UniversityZhuhaiChina

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