Nonlinear Image Enhancement Based on Non-sub-sampled Shearlet Transform and Phase Stretch Transform
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.
KeywordsImage 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.
- 3.Dong L, Bing Y, Mei Y, et al. Image enhancement based on the nonsubsampled contourlet transform and adaptive threshold. Acta Electronica Sin. 2008;36(5):527–30.Google Scholar
- 8.Fan J, Wu Y, Wang F, et al. SAR image registration using phase congruency and nonlinear diffusion-based SIFT. IEEE Geosci Remote Sens Lett. 2014;12(3):562–6.Google Scholar