无人机影像匹配点云单木识别算法

针对单木识别研究中“局部最大值”算法因窗口大小设置不同而产生的单木漏识别与错识别问题，提出了联合“局部最大值”与“单木树冠结构分析”的单木识别算法。算法首先利用“局部最大值”获得候选单木；然后对候选单木树冠结构进行分析，提取树冠结构曲线；最后通过对树冠结构曲线判别，剔除、合并错识别与过识别单木，从而提高单木识别的精度。选取大兴安岭林区８个典型样地进行实验，以实测可见单木为参考，与窗口大小为1.0 m、2.0 m 的两种“局部最大值”算法进行比较。结果表明，该算法8个样地整体F 测度为90.45％，相比1.0 m、2.0 m 窗口的“局部最大值”法F 测度74.82％、77.35％，分别提高，15.63％，13.10％。

Applications of Wavelet Analysis to Remote Sensing Image Processing

This paper studied the latest applications in the field of remote sensing image analysis based on wavelet using classification method. The characteristics and validity of wavelet analysis in remote sensing image processing, such as image compression and coding, remote sensing image fusion, image edge detecting and texture information extracting were analyzed. Application tendency of wavelet in remote sensing is discussed, and some problems about image processing with wavelet analysis, which have not been solved, are also presented.