基于双密度双树复数小波和模糊优化的声呐图像目标增强方法研究

TARGET ENHANCEMENT METHOD OF SONAR IMAGE BASED ON DUAL DENSITY DUAL TREE COMPLEX WAVELET AND FUZZY OPTIMIZATION

  • 摘要: 为了更好地消除噪声对声呐图像的影响,提高声呐图像目标的识别质量,提出一种双密度双树复数小波变换(DDDTCWT)和模糊优化的方法。该方法通过双树结构消除因间隔采样丢失实用信息的缺陷,对分解后的低频分量采用改进的模糊优化算法,对高频分量进行双变量收缩函数处理,经过逆小波变换,得到增强后的图像。经实验证明,该算法能够较好地保留图像的细节信息,使图像的层次更加分明,并有很好的视觉效果。该算法的主观效果和客观指标明显优于其他算法。

     

    Abstract: In order to eliminate the influence of noise on sonar image and improve the recognition quality of sonar image, a method of dual-density dual-tree complex wavelet transform (DDDTCWT) and fuzzy optimization is proposed. The method eliminated the defect of losing practical information due to interval sampling by dual-tree structure, adopted the improved fuzzy optimization algorithm for the decomposed low-frequency components, and performed the dual-variable contraction function processing for the high-frequency components. The enhanced image was obtained through inverse wavelet transform. Experiments show that the proposed algorithm can better retain the details of the image, can make the image level more clear, and has a very good visual effect. The subjective effect and objective index of this algorithm are obviously better than other algorithms.

     

/

返回文章
返回