基于张量投票的激光扫描数据修复方法

Laser scanning data inpainting method based on tensor voting technique

考虑到张量投票技术能够提供图像的几何结构信息,提出一种基于张量投票的激光扫描数据修复方法。首先根据张量投票技术,建立图像修复优先级,进而根据窗口内有效像素和无效像素的比例,用迭代的方法修复具有最大优先权的待修复像素。由于窗口自动选取,因而这种方法具有良好的实用性。实验结果表明,与常用方法相比,所提算法具有良好的修复效果。

Laser scanning works by rapidly firing laser beams downwards to the ground to measure the time which the light takes to reflect from objects located on the ground, and then returning to the laser scanner. It is an active method to directly obtain high-precision three dimensional data and has become an established technique for acquiring geometric information. Due to several reasons of the imagery procedure, the acquired image data are often incomplete, which causes the difficulty for the tasks such as feature extracting, image segmentation and object recognition. Considering that tensor voting techniques can provide the geometric information for an image, a laser scanning inpaniting method based on tensor voting technique is described. First, an inpainting prior level is established, second, the damaging point is inpainted based on the percentage of valid and invalid pixels by an iterative scheme for the highest prior level. Because the window size involved in the inpainting procedure is adjusted automatically, so this method is banausic in practice. The experimental results show that the proposed method has favorable inpainting performance compared with the common inpainting method.