@article{2861,
  author = {Yang Li, Shengyong Chen, Wei Huang},
  title = {Adaptive Noise Image Enhancement Method Based on Genetic Algorithm in Nonsubsampled Contourlet Domain},
  journal = {Journal of Multimedia Processing and Technologies},
  year = {2019},
  volume = {10},
  number = {4},
  doi = {https://doi.org/10.6025/jmpt/2019/10/4/138-151},
  url = {http://www.dline.info/jmpt/fulltext/v10n4/jmptv10n4_2.pdf},
  abstract = {In order to suppress the noise adaptively while enhancing the image details, an adaptive image enhancement
method based on genetic algorithm in Nonsubsampled Contourlet (NSCT) domain is proposed. The optimal parameters of the
image enhancement function are obtained adaptively through genetic algorithm (GA). The NSCT high frequency sub-bands
coefficients are processed by the image enhancement function, the coefficients which are less than the low threshold are set to
0 and the coefficients between the low threshold and the high threshold are enhanced. Experimental results demonstrate that
the proposed method can adaptively enhance the image details and suppress noise at the same time, the detail variance is
significantly improved, and a better visual effect is obtained. The results processed by the proposed method are better than that
by classical enhancement methods.},
}