Geo-registration and mosaic of UAV video for quick-response to forest fire disaster

Jun Wu; Zhongkui Dong; Guoqing Zhou

doi:10.1117/12.748824

15 November 2007 Geo-registration and mosaic of UAV video for quick-response to forest fire disaster

Jun Wu, Zhongkui Dong, Guoqing Zhou

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678810 (2007) https://doi.org/10.1117/12.748824
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

UAV Video is rapidly emerging as a widely used source of imagery for many applications in recent years. This paper presents our research on the UAV video processing system for the purpose of fire surveillance, which include: (1) UAV video stream processing. This step involves three aspects: decoding, re-sampling and matching. Microsoft(R) DirectX(R) technology is used to decode highly compressed video stream and re-sampled them into still video frame based on the time base and rate of UAV navigation sensor. One feature-based image-matching algorithm is developed to quickly obtain Tie points for latter calibration operation. (2) UAV system orientation. This step also involves three aspects: Camera IOP, Boresight Alignment and bundle adjustment. TSAI's two-stage technique is used to obtain initial camera focus length f, distortion coefficients k₁ and six Exterior Of Parameter (EOP) for one selected video image. Meanwhile, the Boresight Matrix is deduced by the comparison of GPS/INS derived parameters with solved EOPs. Further more, all parameters including EOPs of all re-sampled video images and camera IOP are optimally estimated based on developed bundle adjustment algorithm. (3) UAV Video geo-registration and mosaic. All re-sampled video frames are geo-registered into uniform geo-reference coordinate frame vice Classic photogrammetric orthorectification model and merge with each other with developed mosaic algorithm. The results demonstrated that the geo-accuracy of mosaic image generated from UAV video can achieve 1-2 pixels in planimetry and its combination with GIS-supported data for fast response to time-critical event, e.g., forest fire, is descried.

Citation Download Citation

Jun Wu, Zhongkui Dong, and Guoqing Zhou "Geo-registration and mosaic of UAV video for quick-response to forest fire disaster", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678810 (15 November 2007); https://doi.org/10.1117/12.748824

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