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图像信息量分析是图像处理的基础,为此,本文研究了三个不同植被覆盖类型区,即多林区(森林覆盖在40％以上)、一般林地分布的丘陵区(森林覆盖10-30％)和农田为主的丘陵与平原区的图像信息量。分析同一地区冬夏两季的图像信息特征后得知,红外波段的信息量高于可见光波段,其中信息量最大的是TM5波段,最小的是TM2波段。同时对不同情况下波段间的相关性、均值和标准差等统计特征值也进行了分析。据此就图像增强、信息特征提取方法,如主成分分析、缨帽变换(KT变换)、比值等方法以及波段组合等进行了系统研究,并就其实用条件进行了探讨和评价。
Image information analysis is the basis of image processing. Therefore, three different types of vegetation cover are studied in this paper, that is, multi-forest area (forest cover more than 40%), general hilly land area (10-30% ) And farmland-based hills and plain areas of the image information. After analyzing the image information characteristics of winter, summer and winter in the same area, we know that the information content of infrared band is higher than that of visible band, among which TM5 band is the most informative and TM2 band is the smallest. At the same time, the statistical eigenvalues of correlation, mean and standard deviation among different bands are also analyzed. Based on this, we systematically study the image enhancement and information feature extraction methods, such as principal component analysis, KT transformation, ratio and other methods as well as band combination, and discuss and evaluate their practical conditions.