A nature scene image color-texture feature extraction method based on human visual system (HVS) was proposed.
提出了基于人类视觉系统的自然场景图像颜色和纹理特征提取方法。
This paper proposes a fast algorithm for texture feature extraction. The new algorithm is suitable for remote image classification on line.
给出一种抽取纹理特征的算法，该算法实时性强，适于在线遥感图像分类。
The excellent characteristics of rotation-invariance, good orientation selection and finite redundancy are fully utilized, and applied in texture feature extraction.
充分利用双树复小波变换的旋转不变性、良好的方向选择性以及有限的冗余等优点，将其有效地应用于纹理特征提取过程中。
A new texture feature extraction method using Local Walsh Transform (LWT) is presented. The definition of LWT is given. The statistical properties of LWT coefficients are analyzed.
介绍了一种利用局部沃尔什变换(LWT)提取图像纹理特征的新方法，给出lwt的定义，并分析了LWT系数的统计特性及其各阶矩的纹理鉴别性能。
Similarly, the work of texture feature extraction is obtained by using co-occurrence matrix or frequency analysis based on wavelet transform depending on different characteristics of images.
在纹理特征提取方面，针对不同纹理特点分别采用了基于共生矩阵的统计纹理分析和基于小波变换的频谱纹理分析两种方法予以实现。
Similarly, the work of texture feature extraction is obtained by using co-occurrence matrix or frequency analysis based on wavelet transform depending on different characteristics of images.
在纹理特征提取方面，针对不同纹理特点分别采用了基于共生矩阵的统计纹理分析和基于小波变换的频谱纹理分析两种方法予以实现。
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