Sub-pixel target mapping from soft-classified, remotely sensed imagery
Sub-pixel target mapping from soft-classified, remotely sensed imagery
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DOI：
10.14358/pers.71.7.839
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发表时间：
2005-07-01
影响因子：
1.3
通讯作者：
Atkinson, PM
中科院分区：
文献类型：
--
作者：
Atkinson, PM
提出了一种简单、有效的遥感图像亚像元目标映射算法。在初始随机分配“软”像素比例到“硬”子像素二进制类之后，该算法以一系列迭代工作，每个迭代包含三个阶段。对于每个像素，对于所有子像素位置，计算相邻子像素的距离加权函数。然后，对于每个像素，找到具有函数的最小值的表示目标类的子像素和具有函数的最大值的表示背景的子像素。新算法对简单的模拟图像和真实的图像的预测精度较高。它是一种可供使用的工具，遥感调查人员可随时对其进行编码和应用。
A simple, efficient algorithm is presented for sub-pixel target mapping from remotely-sensed images. Following an initial random allocation of "soft" pixel proportions to "hard" sub-pixel binary classes, the algorithm works in a series of iterations, each of which contains three stages. For each pixel, for all sub-pixel locations, a distance-weighted function of neighboring sub-pixels is computed. Then, for each pixel, the sub-pixel representing the target class with the minimum value of the function, and the sub-pixel representing the background with the maximum value of the function are found. Third, these two sub-pixels are swapped if the swap results in an increase in spatial correlation between sub-pixels. The new algorithm predicted accurately when applied to simple simulated and real images. It represents an accessible tool that can be coded and applied readily by remote sensing investigators.