基于LBP的多光谱图像纹理特征提取方法

摘要

The result of feature extraction on multi-spectral image is directly related to the complex degree of target recognition algorithm. And the performance of final target recognition is also influenced. The traditional local binary pattern (LBP) feature extraction method is researched. And several new LBP feature such as direc-tional LBP feature describer, adaptive LBP feature describer and directional adaptive feature describer are intro-duced. And they are applied to texture features extraction of multi-spectral images. Experimental results show that LBP feature describer and its improvement methods are very suitable for extracting the texture features of multi-spectral images.%多光谱图像特征提取的好坏直接关系着目标识别算法的复杂程度，也影响着最终目标识别的性能。研究了经典的局部二元模式(local binary pattern, LBP)特征提取方法，并引入了几种新的LBP特征，包括：方向LBP特征描述子、自适应LBP特征描述子和方向自适应特征描述子，应用于多光谱图像纹理特征提取。实验结果表明，LBP特征描述子及其改进方法都非常适合于多光谱图像的纹理特征提取。