Stereo image scale difference estimation and matching optimization in parallel tunnel photogrammetry
In pursuit of heightened accuracy in matching homologous points within parallel tunnel sequence images,this paper delved into the realms of imaging perspective and matching methodologies.A novel automated scale correction approach,rooted in the Lucas-Kanade(LK)optical flow method and implemented within a predefined window,was introduced.The core concept in-volved constructing a scale difference model based on the spatial relationship between the object and its image,coupled with the u-tilization of a variable window for tracking feature points'optical flow.The obtained results revealed a symmetric radial distribution of scale differences in tunnel sequence images,with difference values adhering to a power-law growth trend.When applied in matching experiments involving stereo image pairs with multiple scale differences,the proposed method consistently obtained ex-periment precision exceeding 0.3 pixels.This method was superior to basic optical flow method,with improvements ranging from 34.3%to 45.5%.These research findings not only contribute references for matching methods that account for scale differences,but also establish a foundation for stereo image matching in parallel tunnel photography.
parallel photographytunnel imagescale differences modeloptical flow methodpower-law model
国家科技期刊平台
NSTL
万方数据
维普
