基于二进小波统计特征的纹理图像检索.pdfVIP

33 20 2007 10 Vol.33 No.20 Computer Engineering October 2007 · · 2007 A TP391.40 1 2 (1. 1000442. 400044) () Manjunath Texture Image Retrieval Based on Statistical Characteristic of Dyadic Wavelet Transform 1 2 ZHAO Ping , SHANG Zhao-wei (1. School of Science, Beijing Jiaotong University, Beijing 100044; 2. College of Computer Science, Chongqing University, Chongqing 400044) AbstractThe dyadic wavelet transform utilizes local modulus maximum of a wavelet transform to obtain multiscale edges information. This paper analyzes the statistical characteristics of the wavelet detail coefficients of the dyadic wavelet transform, and brings forward the wavelet coefficients histogram of nature texture image which can be modeled by a family of exponentials. It studies the ways to extract the texture features using the first-order and second-order (co-occurrence) based on the dyadic wavelet transform. Experimental results show that methods of Manjunath and second-order of the dyadic wavelet are better than that of scalar wavelet on texture image retrieval. Key wordsdyadic wavelet transform; texture; co-occurrence matrix; statistical characterization; texture retrieval 1 2 Gabor [3] GaborGabor h(u) Ke−(|u|/ α)β (1