程起敏, 杨崇俊, 邵振峰. 基于多进制小波变换的渐进式纹理图像检索[J]. 武汉大学学报 ( 信息科学版), 2005, 30(6): 521-524.
引用本文: 程起敏, 杨崇俊, 邵振峰. 基于多进制小波变换的渐进式纹理图像检索[J]. 武汉大学学报 ( 信息科学版), 2005, 30(6): 521-524.
CHENG Qimin, YANG Chongjun, SHAO Zhenfeng. Progressive Texture Image Retrieval Based on M-Band Wavelet Features[J]. Geomatics and Information Science of Wuhan University, 2005, 30(6): 521-524.
Citation: CHENG Qimin, YANG Chongjun, SHAO Zhenfeng. Progressive Texture Image Retrieval Based on M-Band Wavelet Features[J]. Geomatics and Information Science of Wuhan University, 2005, 30(6): 521-524.

基于多进制小波变换的渐进式纹理图像检索

Progressive Texture Image Retrieval Based on M-Band Wavelet Features

  • 摘要: 提出了一种基于多进制小波变换的渐进式纹理图像检索方法,纹理图像的特征通过多进制小波分解结果来描述,用低频子图小波系数标准方差和多进制小波直方图结合相应的相似性距离函数,实现目标图像数据库由粗到精的渐进式检索。通过Bordatz和USC纹理图像数据库来检验本方法的精度和效率,获得了较理想的试验结果。

     

    Abstract: A M-band-wavelet-based features for progressive texture image retrieval method is presented. The information of a texture image is acquired through M-band wavelet decomposition of the original image. The integration of two feature descriptors, wavelet-coefficient standard deviation of the approximation sub-image and M-band wavelet histogram, and their corresponding distance similarity measure functions are used to realize progressive retrieval of target texture image databases. Finally, a texture database obtained from Bordatz album and USC image database is used to check the retrieval performance of the proposed method.

     

/

返回文章
返回