DOI QR코드

DOI QR Code

Seamline Detection for Image Mosaicking with Image Pyramid

영상 피라미드 기반 영상 모자이크를 위한 접합선 추출

  • 유은진 (LX한국국토정보공사 공간정보연구원)
  • Received : 2023.08.18
  • Accepted : 2023.09.14
  • Published : 2023.09.30

Abstract

Image mosaicking is one of the basic and important technologies in the field of application using images. The key of image mosaicking is to extract seamlines from a joint image. The method proposed in this paper for image mosaicking is as follows. The feature points of the images to be joined are extracted and the joining form between the two images is identified. A reference position for detection the seamlines were selected according to the joint form, and an image pyramid was created for efficient image processing. The outlines of the image including buildings and roads are extracted from the overlapping area with low resolution, and the seamlines are determined by considering the components of the outlines. Based on this, the seamlines in the high-resolution image was re-searched and finally the seamline for image mosaicking was determined. In addition, in order to minimize color distortion of the image with the determined seamline, a method of improving the quality of the mosaic image by fine correction of the mosaic area was applied. It was confirmed that the quality of the seamline extraction results applying the method proposed was reasonable.

Keywords

References

  1. Adelson, E.H., Anderson, C.H., Bergen, J.R., Burt, P.J., and Ogden, J.M., Pyramid Methods in Image Processing, RCA Engineer, 1984, Vol. 29, No. 6, pp. 33-41.
  2. Bay, H., Ess, A., Tuytelaars, T., and Gool, L.V., Speeded-Up Robust Features(SURF), Computer Vision and Image Understanding, 2008, Vol. 110, No. 3, pp. 346-359. https://doi.org/10.1016/j.cviu.2007.09.014
  3. Chai, X., Chen, J., Mao, Z., and Zhu, Q., An Upscaling-Downscaling Optimal Seamline Detection Algorithm for Very Large Remote Sensing Image Mosaicking, Remote Sensing, 2022, Vol. 15, No. 1, p. 89.
  4. Chen, Q., Sun, M., Hu, X., and Zhang, Z., Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model, Remote Sensing, 2014, Vol. 6, No. 12, pp. 12334-12359. https://doi.org/10.3390/rs61212334
  5. Choi, J., Jung, H., and Yun, S., An Efficient Mosaic Algorithm Considering Seasonal Variation: Application to KOMPSAT-2 Satellite Images, Sensors, 2015, Vol. 15, No. 3, pp. 5649-5665. https://doi.org/10.3390/s150305649
  6. Fischler, M. and Bolles, R., Random Sample Consensus: a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography, Communications of the ACM, 1981, Vol. 24, No. 6, pp. 381-395. https://doi.org/10.1145/358669.358692
  7. John, C., A Computational Approach to Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, Vol. 8, No. 6, pp. 679-698. https://doi.org/10.1109/TPAMI.1986.4767851
  8. Kim, D.H., Oh, C.Y., Lee, D.G., and Lee, D.C., Seamline Determination from Images and Digital Maps for Image Mosaicking, Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 2018, Vol. 36, No. 6, pp. 483-497.
  9. Li, L., Yao, J., Lu, X., Tu, J., and Shan, J., Optimal Seamline Detection for Multiple Image Mosaicking via Graph Cuts, ISPRS Journal of Photogrammetry and Remote Sensing, 2016, Vol. 113, No 1, pp. 1-16. https://doi.org/10.1016/j.isprsjprs.2015.12.007
  10. Nguyen, T. and Han, D., Thermal Image Mosaicking Using Optimized FAST Algorithm, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography, 2017, Vol. 35, No. 1, pp. 41-53.
  11. Oh, K., Jung, H., Lee, K., and Lee, H., A Method for Quantitative Quality Assessment of Mosaic Imagery, Korean Journal of Remote Sensing, 2014, Vol. 30, No. 1, pp. 1-12. https://doi.org/10.7780/KJRS.2014.30.1.1
  12. Perona, P. and Malik, J., Scale-space and Edge Detection Using Anisotropic Diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, Vol. 12, No. 7, pp. 629-639. https://doi.org/10.1109/34.56205
  13. Wang, M., Yuan, S., Pan, J., Fang, L., Zhou, Q., and Yang, G., Seamline Determination for High Resolution Orthoimage Mosaicking Using Watershed Segmentation, Photogrammetric Engineering and Remote Sensing, 2016, Vol. 82, No. 2, pp. 121-133. https://doi.org/10.14358/PERS.82.2.121
  14. Yuan, S., Yang, K., Li, X., and Cai, H., Automatic Seamline Determination for Urban Image Mosaicking Based on Road Probability Map from the D-LinkNet Neutral Network, Sensors, 2020, Vol. 20, No. 7, p. 1832.
  15. Zhang, W., Guo, B., Li, M., Liao, X., and Li, W., Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow, Sensors, 2018, Vol. 18, No. 4, p. 1214.