中文摘要：

鉴于多/高光谱遥感数据同源同点多波段同时获取的特点,提出了基于灰度级差关联概率矩阵（Gray Level Difference Associated Possibility matrix,GLDAP）的视觉差异分析方法,以有效地利用图像底层数据及数据之间的相关性.根据地物的波谱特性,统计两波段图像灰度协同变化的规律并记录在GLDAP矩阵中,基于此矩阵提取了遥感数据的类立体纹理特征.将该方法与灰度共生矩阵（GLCM）纹理分析方法的遥感地物分类性能比较,实验结果表明：基于GLDAP的纹理提取及分析表现出良好的性能,3种地物分类效果明显优于GLCM方法,能够减少因单波段中地物可分性差而导致的误识,克服了GLCM方法对图像统计描述的局限性,在相同时间开销下GLDAP方法较GLCM有更优的解译分析精度.

英文摘要：

According to the synchronous acquirement of multi-,hyper-spectral remote sensed imagery,a Gray Level Difference Associated Possibility matrix（GLDAP） method is proposed in the paper to analyze visual differences between multi-band data.The matrix is built on two bands of image that are selected in light of land-cover spectrum characteristics.Thereafter,the co-varying statistics of gray level in each image is recorded and quasi-3-dimention texture features are extracted based on GLDAP.During experiments,GLDAP is employed in classifications and annotations of land cover types,compared with GLCM method.The results reveal that the GLDAP has better performances than GLCM.Moreover,it could overcome the limitation of single band processing and understanding,on which GLCM based,and to a certain degree,decrease misrecognition rate caused by worse visual discrimination of land types at data level.The two methods have same time complexity;hence,GLDAP may be accepted as another choice in getting excellent precision and better performance under the same time consuming.