方向无关遥感影像的纹理分类算法

首先根据遥感影像空间分辨率较低，局部区域内图像纹理变化不大的特点，对遥感影像进行合理的分块，使得各分块具有单一的主纹理特征；然后利用Gabor小波变换提取各图像块的纹理特征向量，并通过简单的循环移位算法，方便的形成方向无关的纹理特征向量；进而引入改进的棋盘距离来描述图像块间的相似度，最后使用无监督聚类算法对影像块进行分类，达到了很好的分类效果．

ROTATION INVARIANT TEXTURE CLASSIFICATION OF REMOTE SENSE IMAGE

The original image was properly divided into unoverlapped blocks according to the small change of texture in local areas of the remote senses image, each of which associated with a uniform texture. Then texture feature of each block was formed by calculating the mean and variance of Gabor filtered image. Rotation normalization was realized by circular shift of the feature elements to get the invariant texture feature vector. The classification of image blocks was also completed by using a simple unsupervised clustering algorithm. The experiments of the real images show that the method is effective.