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This paper designs a technique route to generate high-quality panoramic imagewith depth information, which involves two critical research hotspots: fusionof LiDAR and image data and image stitching. For the fusion of 3D points andimage data, since a sparse depth map can be firstly generated by projectingLiDAR point onto the RGB image plane based on our reliable calibrated andsynchronized sensors, we adopt a parameter self-adaptive framework to produce2D dense depth map. For image stitching, optimal seamline for the overlappingarea is searched using a graph-cuts-based method to alleviate the geometricinfluence and image blending based on the pyramid multi-band is utilized toeliminate the photometric effects near the stitching line. Since each pixel isassociated with a depth value, we design this depth value as a radius in thespherical projection which can further project the panoramic image to the worldcoordinate and consequently produces a high-quality measurable panoramic image.The purposed method is tested on the data from our data collection platform andpresents a satisfactory application prospects.

A Method of Generating Measurable Panoramic Image for Indoor Mobile Measurement System