Nonlinear Image Enhancement Based on Non-sub-sampled Shearlet Transform and Phase Stretch Transform

  • Ying Tong
  • Kaikai Li
  • Jin ChenEmail author
  • Rong Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 516)


In this paper, non-sub-sampled shearlet transform (NSST) multi-scale analysis is combined with phase stretch transform (PST) to nonlinearly enhance images. The components of different scales after NSST multi-scale decomposition are processed by nonlinear models with different thresholds, and the noise is well suppressed while enhancing the detail features. The thresholds of the enhanced model are determined by the local standard deviation of PST feature map. Experiments on Matlab platform show that the proposed algorithm has improved image distortion, cleared details, and enhanced image contrast.


Image enhancement Non-sub-sampled shearlet transform Phase stretch transform Nonlinear function 



This work was supported by National Natural Science Foundation of China (Grant No: 61701344), Tianjin Edge Technology and Applied Basic Research Project (14JCYBJC15800) in China, Tianjin Normal University Application Development Foundation (52XK1601), Tianjin Normal University Doctoral Foundation (52XB1603, 52XB1713), and Tianjin Higher Education Creative Team Funds Program in China.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Tianjin Key Laboratory of Wireless Mobile Communications and Power TransmissionTianjin Normal UniversityTianjinChina
  2. 2.College of Electronic and Communication EngineeringTianjin Normal UniversityTianjinChina

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