• DocumentCode
    2835481
  • Title

    Image enhancement based on improved genetic algorithm and lifting wavelet method

  • Author

    Song, Chuanjun ; Gao, Bingkun ; Kan, Lingling ; Liang, Hongwei

  • Author_Institution
    Sch. of Electr. Inf. Eng., Daqing Pet. Univ., Daqing, China
  • fYear
    2010
  • fDate
    26-28 May 2010
  • Firstpage
    893
  • Lastpage
    895
  • Abstract
    An image enhancement algorithm based on genetic algorithm and lifting wavelet method is proposed in this paper. This algorithm improves crossover operation algorithm. It utilizes average displacement method for mutation operation. Probabilities of crossover and mutation are selected adaptively. We have decided the fitness function, and have implemented multi-thread design. The algorithm optimizes the prediction and updating operator of lifting wavelet by means of genetic algorithm. The decision of the prediction and updating operator is improved. The contrast ration between the object and background is increased. The details of images are reserved well. The background noise is reduced, and the algorithm is very efficient.
  • Keywords
    genetic algorithms; image enhancement; probability; wavelet transforms; average displacement; background noise; crossover operation; crossover probability; fitness function; genetic algorithm; image enhancement; lifting wavelet method; multithread design; mutation operation; mutation probability; Biological cells; Genetic algorithms; Genetic engineering; Genetic mutations; Image enhancement; Noise reduction; Partitioning algorithms; Petroleum; Prediction algorithms; Wavelet transforms; Image Enhancement; Improved Genetic Algorithm; Lifting Wavelet; Multi-thread;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2010 Chinese
  • Conference_Location
    Xuzhou
  • Print_ISBN
    978-1-4244-5181-4
  • Electronic_ISBN
    978-1-4244-5182-1
  • Type

    conf

  • DOI
    10.1109/CCDC.2010.5498098
  • Filename
    5498098