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陆地卫星图像的磁带数码值或扫描密度值,均可被转换成绝对辐射值。四个波段中的每一波段的辐射值,均可分解为具有不同物理意义的三部分,其中,四个波段中物理意义相同的那一部分,又可被重新组合起来,于是,便得到三个新变量。它们分别被命名为总辐射水平值L,可见-红外(辐射)平衡值B,和波段(辐射)变化向量值V。L能监测地物的辐射强度;B能监测水、水分和地表层的潮湿程度,并能区分云、雪和冰;V能监测植被的密度与生活力,因而是植被状况的良好指标。这三个变量几乎包含了原四个波段的全部信息,因此,通常只需处理这三个变量。算法基于回归分析且维数低,因此十分简单。因而,可节省图像处理时间和费用。使用这个方法,可以获得真正三色的、接近于自然色彩的真彩色合成图像,还可获得相应于地物特征的有意义的密度分割图像。此方法已被应用于中国和世界范围内的遥感资料。
Land satellite image of the tape digital or scanning density values, can be converted into absolute radiation value. The radiation values of each of the four bands can be decomposed into three parts of different physical meaning, of which the four parts of the same physical meaning can be recombined, so that three New variable They are respectively named the total radiation level L, visible - infrared (radiation) balance B, and the band (radiation) change vector V. L can monitor the radiation intensity of the ground object; B can monitor the moisture level of water, moisture and surface layer, and can distinguish between cloud, snow and ice; V can monitor vegetation density and viability and therefore is a good indicator of vegetation status. These three variables contain almost all of the original four bands of information, therefore, usually only deal with these three variables. The algorithm is based on regression analysis and has low dimensions, so it’s easy. Thus, image processing time and cost can be saved. With this method, you can get true trichromatic, close-to-natural color composite images, and meaningful density-segmented images that correspond to features. This method has been applied to remote sensing data in China and in the world.