Adaptive typhoon cloud image enhancement using genetic algorithm and non-linear gain operation in undecimated wavelet domain

  • Authors:

  • Changjiang Zhang;Xiaodong Wang;Chunjiang Duanmu

  • Affiliations:

  • College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, Zhejiang Province 321004, China and State Key Laboratory of Remote Sensing Science, Jointly Sponsor ...;College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, Zhejiang Province 321004, China;College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, Zhejiang Province 321004, China

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

By combining discrete undecimated wavelet transform (UWT) with genetic algorithm (GA) an efficient enhancement algorithm for typhoon cloud image is proposed. Having implemented UWT to a typhoon cloud mage, noise in a typhoon cloud image is reduced by modifying the undecimated wavelet coefficients by combining with generalization cross validation at fine resolution levels. GA and non-linear gain operation are used to modify the undecimated wavelet coefficients at coarse resolution levels in order to extrude the details of a typhoon cloud image. Experimental results show that the proposed algorithm can efficiently reduce the additive gauss white noise in a typhoon cloud image while well extruding the detail. In order to accurately assess an enhanced typhoon cloud image's quality, an overall score index is proposed based on information entropy, contrast measure and peak signal-noise ratio. Finally, comparisons between the proposed algorithm and five other similar methods, are carried out.