Automatic image matching for space intersection of spherical panorama images

Pin Yun Chen, Yi Hsing Tseng, Kuan Ying Lin

Research output: Contribution to conferencePaperpeer-review

Abstract

People are paying more attention to the use of Spherical Panorama Images (SPIs) for its main advantage of wide field of view (FOV). Provide accurate location and orientation can enhance more metric application using SPIs. While the exterior orientation parameters (EOPs) of image stations are known, the coordinates of interested points can be determined by space intersection of multiple SPIs. In this study, a special platform called portable panoramic image mapping system (PPIMS) is used to obtain SPIs, and applied for photogrammetric mapping. This system equips with eight single lens cameras and one GNSS receiver, capturing surrounding information simultaneously. The images captured with PPIMS are combined to be a SPI, and then used for mapping application instead of using original images. The EOPs of image stations can be calculated by the network adjustment with multiple SPIs. No matter in solving image station EOPs or space intersection process, conjugate points selection among overlapped images is a necessary task. Image matching is considered as an approach to obtain conjugate points much more efficient than manual measurement. In this study, an area-based image matching strategy for automatic conjugate point detection and point coordinate determination with multiple SPIs is proposed. The Sum of Normalized Cross-Correlation (SNCC) and Yet Another Reconstruction Dataprogram (YARD) index are used to check the similarity between images. To decrease the influence caused by scale variations and different FOV between images, the concept of matching in the object space is applied to enhance the matching accuracy. This research shows the feasibility of spatial positioning of interested points with PPIMS SPIs in cm level accuracy. The proposed image matching strategy with PPIMS SPIs is applied and validated. The problem of scale variations and different FOV which causes problem in matching with original images can be improved by object space matching.

Original languageEnglish
Publication statusPublished - 2017
Event38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017 - New Delhi, India
Duration: 2017 Oct 232017 Oct 27

Other

Other38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017
CountryIndia
CityNew Delhi
Period17-10-2317-10-27

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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