The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 m resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5 satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of China. 相似文献
The accurate estimation of the end-effector’s pose in large operating spaces is the key for the mobile manipulator to realize efficient manufacturing of large and complex components. We propose a novel pose tracking method in large-range using visual fiducial markers, and further propose the layout optimization method for the encoded fiducial markers. A metric named orientational dilution of precision (ODOP) is proposed to evaluate the magnification of the pose estimation error compared with the measurement error of the coded fiducial markers. The distribution pattern of the coded markers is analyzed based on ODOP, and the square-shaped layout is determined to be a satisfactory distribution pattern for the minimum positioning unit of markers, and the side length of the square-shaped layout is further selected. The simulations and experiments prove the effectiveness of the ODOP index. Finally, the square-shaped layout and the designed distribution density for positioning coded markers are adopted to realize the high-precision measurement of large components by the mobile manipulator.
