Title

以影像邊緣線資訊優化真實正射影像

Translated Titles

Optimize True Ortho Images with Image Edge Line Information

DOI

10.6342/NTU201801614

Authors

陳立恒

Key Words

真實正射影像 ; 建物屋頂邊緣線萃取 ; 無人飛行載具 ; True-Ortho Images ; Building Roof Extraction ; Unmanned Aerial Vehicle

PublicationName

臺灣大學土木工程學研究所學位論文

Volume or Term/Year and Month of Publication

2018年

Academic Degree Category

碩士

Advisor

徐百輝

Content Language

繁體中文

Chinese Abstract

近年來,隨著無人飛行載具的快速發展,在測量製圖的應用尤為顯著,無人 飛行載具具有高機動性、低成本的優勢,且可以在低空雲下作業,相較於傳統航 遙測載具所受到天候及雲層遮蔽的影響較小。傳統航遙測影像進行正射校正,所 產生之正射影像與地圖具備正射投影、單一比例尺之幾何特性,因此可以在正射 影像上直接獲取幾何資訊,也可以與地理資訊系統應用結合。隨著軟、硬體快速 發展,無論是利用空載航照或是衛星影像根據 DEM 校正產生正射影像都已逐 漸普及。有別於傳統正射影像未對建物之高差位移進行修正,真實正射校正考量 所有地表物體在影像的幾何變形與遮蔽,透過數值地表模型校正後之成果影像可 以展示所有地表覆蓋物的「真實位置」,故稱為真實正射校正。藉由高解析度影 像匹配所獲得的數值地表模型,在邊緣線位置以及高程變化處容易產生扭曲或不 連續的現象,連帶導致其產製之真實正射影像邊緣線扭曲情形。主要原因為點雲 密匹配之誤差,以及點雲內插 DSM 所產生的扭曲的情形,因此需對數值地表模 型進行精化,使遮蔽區的偵測能夠正確且不會有扭曲的情形產生,本研究將利用 原始航拍影像,以及密匹配得到之點雲成果,從原始航拍影像找出真正建物邊緣線位置,並對於 DSM 進行修正。

English Abstract

As the rapid growth of the Unmanned Aerial Vehicle(UAV), the application in surveying and mapping is more and more popular. In contrast with conventional remote sensing and photogrammetric images which are restricted by weather conditions, the advantages of UAV include high mobility, low cost and flying capability beneath cloud. On orthoimages prodecued by photogrammetry, we can acquire lots of spatial information, such as distance, angle and area. Because orthoimages are rectified according to DEM, the relief displacement caused by building can bot be modified. The so called true orthoimages which are rectified by DSM (digital surface model) are free from the distortion caused by the relief displacement. However, DSM generated by stereo dense matching may have mismatches especially along the edge of building roofs, thus reduces the quality of true orthoimages. To overcome this problem, this study proposed a procedure which firstly finds the exact building roof edge from original UAV images, and then the mismatches of DSM are modified to produce high quality true orthoimages.

Topic Category 工學院 > 土木工程學研究所
工程學 > 土木與建築工程
Reference
  1. 李柏翰,2007基於多視角影像擷取之三維模型重建系統開發。
  2. 李訢卉,2007。 整合房屋、道路及地形模型之高解析影像正射改正。中央大學土木工程學系學位論文, pp.1-92。
  3. 李硯婷, & 蔡展榮,2014。空照影像密匹配成果偵錯之瓶頸與解決辦法。
  4. 林迪詒, & 謝嘉聲,2017。 利用 SGM 和 PMVS 演算法進行 MUAV 影像密匹配之比較分析. Journal of Photogrammetry and Remote Sensing, 22(3), 193-203.
  5. 洪曉竹, 曾義星, &朱宏杰。2013。 應用空載光達資料自動化萃取建物邊界線,國立成功大學博士論文。
  6. 張智安,2008,整合光達點雲與地形圖模塑建物之分治策略,國立中央大學博士論文,pp.1-119。
  7. 湯美華,2006。空載光達點雲及地形圖輔助生產 真實正射影像之研究。碩士論文,國立成功大學土木工程研究所碩士論文,pp.1-29。
  8. Amhar, F., Jansa, J., & Ries, C. (1998). The generation of true orthophotos using a 3D building model in conjunction with a conventional DTM. International Archives of Photogrammetry and Remote Sensing, 32, 16-22.
  9. Arun, P. V. (2013). A comparative analysis of different DEM interpolation methods. The Egyptian Journal of Remote Sensing and Space Science, 16(2), 133-139.
  10. Bang, K. I., Habib, A. F., Shin, S. W., & Kim, K. O. (2007). Comparative analysis of alternative methodologies for true ortho-photo generation from high resolution satellite imagery. ASPRS ANNUAL, 2007.
  11. Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9), 509-517.
  12. Bradski, G., & Kaehler, A. (2008). Learning OpenCV: Computer vision with the OpenCV library. " O'Reilly Media, Inc.".
  13. Canny, J. (1986). A computational approach to edge detection. Pattern Analysis and
  14. Machine Intelligence, IEEE Transactions on, (6), 679-698
  15. Chen, L. C., Teo, T. A., Wen, J. Y., & Rau, J. Y. (2007). Occlusion‐Compensated True Orthorectification For High‐Resolution Satellite Images. The Photogrammetric Record, 22(117), 39-52.
  16. Chen, Y., Briese, C., Karel, W., & Pfeifer, N. (2014). True orthophoto generation using multi-view aerial images. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(3), 67.
  17. Dare, P. M. (2005). Shadow analysis in high-resolution satellite imagery of urban areas. Photogrammetric Engineering & Remote Sensing, 71(2), 169-177.
  18. Dornaika, F., Moujahid, A., El Merabet, Y., & Ruichek, Y. (2016). Building detection from orthophotos using a machine learning approach: An empirical study on image segmentation and descriptors. Expert Systems with Applications, 58, 130-142.
  19. Douglas, D. H., & Peucker, T. K. (1973). Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica: The International Journal for Geographic Information and Geovisualization, 10(2), 112-122.
  20. Furukawa, Y., & Ponce, J. (2010). Accurate, dense, and robust multiview stereopsis. IEEE transactions on pattern analysis and machine intelligence, 32(8), 1362-1376.
  21. Habib, A. F., Kim, E. M., & Kim, C. J. (2007). New methodologies for true orthophoto generation. Photogrammetric Engineering & Remote Sensing, 73(1), 25-36.
  22. Hirschmuller, H. (2005, June). Accurate and efficient stereo processing by semi-global matching and mutual information. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on (Vol. 2, pp. 807-814). IEEE.
  23. Hu, J., You, S., Neumann, U., & Park, K. K. (2004, May). Building modeling from LiDAR and aerial imagery. In ASPRS (Vol. 4, pp. 23-28).
  24. Kim, Z., Huertas, A., & Nevatia, R. (2001). Automatic description of buildings with complex rooftops from multiple images. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on (Vol. 2, pp. II-II). IEEE.
  25. Maini, R., & Aggarwal, H. (2009). Study and comparison of various image edge detection techniques. International journal of image processing (IJIP), 3(1), 1-11.
  26. Naoum, S., & Tsanis, I. K. (2004). Ranking spatial interpolation techniques using a GIS-based DSS. Global Nest, 6(1), 1-20.
  27. Ngo, T. T., Collet, C., & Mazet, V. (2015,). Automatic rectangular building detection from VHR aerial imagery using shadow and image segmentation. In Image Processing (ICIP), 2015 IEEE International Conference on (pp. 1483-1487). IEEE.
  28. Nielsen, M. Ø. (2004). True orthophoto generation (Master's thesis, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark).
  29. Oda, K., Lu, W., Uchida, O. and Doihara, T., 2004. “Triangle-based Visibility Analysis and True Orthoimage Generation”. Int. Arch. Photogrammetry, Remote Sensing and Spatial Information, Vol.35 (3) pp.623-628.
  30. Ortner, M., Descombes, X., Zerubia, J., 2007. Building outline extraction from digital elevation models using marked point processes, International Journal of Computer Vision, 72(2), 107–132.
  31. Sampath, A. and Shan, J., 2007. Building boundary tracing and regularization from airborne lidar point clouds, Photogrammetric Engineering and Remote Sensing, 73(7): 805-812.
  32. San A, D. K. (2007). Automatic building extraction from high resolution stereo satellite images.
  33. Sun, S., & Savalggio, C. (2012,). Complex building roof detection and strict description from LiDAR data and orthorectified aerial imagery. In Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International (pp. 5466-5469). IEEE.
  34. Rafael, C. G., and Richard, E. W. (2002,). Digital Image Processing 2nd edition, Addison-Wesley, Tokyo, pp.555-574.
  35. Zhou, G., Chen, W., Kelmelis, J. A., & Zhang, D. (2005). A comprehensive study on urban true orthorectification. IEEE Transactions on Geoscience and Remote sensing, 43(9), 2138-2147.
  36. 李柏翰,2007基於多視角影像擷取之三維模型重建系統開發。
  37. 李訢卉,2007。 整合房屋、道路及地形模型之高解析影像正射改正。中央大學土木工程學系學位論文, pp.1-92。
  38. 李硯婷, & 蔡展榮,2014。空照影像密匹配成果偵錯之瓶頸與解決辦法。
  39. 林迪詒, & 謝嘉聲,2017。 利用 SGM 和 PMVS 演算法進行 MUAV 影像密匹配之比較分析. Journal of Photogrammetry and Remote Sensing, 22(3), 193-203.
  40. 洪曉竹, 曾義星, &朱宏杰。2013。 應用空載光達資料自動化萃取建物邊界線,國立成功大學博士論文。
  41. 張智安,2008,整合光達點雲與地形圖模塑建物之分治策略,國立中央大學博士論文,pp.1-119。
  42. 湯美華,2006。空載光達點雲及地形圖輔助生產 真實正射影像之研究。碩士論文,國立成功大學土木工程研究所碩士論文,pp.1-29。
  43. Amhar, F., Jansa, J., & Ries, C. (1998). The generation of true orthophotos using a 3D building model in conjunction with a conventional DTM. International Archives of Photogrammetry and Remote Sensing, 32, 16-22.
  44. Arun, P. V. (2013). A comparative analysis of different DEM interpolation methods. The Egyptian Journal of Remote Sensing and Space Science, 16(2), 133-139.
  45. Bang, K. I., Habib, A. F., Shin, S. W., & Kim, K. O. (2007). Comparative analysis of alternative methodologies for true ortho-photo generation from high resolution satellite imagery. ASPRS ANNUAL, 2007.
  46. Bentley, J. L. (1975). Multidimensional binary search trees used for associative searching. Communications of the ACM, 18(9), 509-517.
  47. Bradski, G., & Kaehler, A. (2008). Learning OpenCV: Computer vision with the OpenCV library. " O'Reilly Media, Inc.".
  48. Canny, J. (1986). A computational approach to edge detection. Pattern Analysis and
  49. Machine Intelligence, IEEE Transactions on, (6), 679-698
  50. Chen, L. C., Teo, T. A., Wen, J. Y., & Rau, J. Y. (2007). Occlusion‐Compensated True Orthorectification For High‐Resolution Satellite Images. The Photogrammetric Record, 22(117), 39-52.
  51. Chen, Y., Briese, C., Karel, W., & Pfeifer, N. (2014). True orthophoto generation using multi-view aerial images. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(3), 67.
  52. Dare, P. M. (2005). Shadow analysis in high-resolution satellite imagery of urban areas. Photogrammetric Engineering & Remote Sensing, 71(2), 169-177.
  53. Dornaika, F., Moujahid, A., El Merabet, Y., & Ruichek, Y. (2016). Building detection from orthophotos using a machine learning approach: An empirical study on image segmentation and descriptors. Expert Systems with Applications, 58, 130-142.
  54. Douglas, D. H., & Peucker, T. K. (1973). Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. Cartographica: The International Journal for Geographic Information and Geovisualization, 10(2), 112-122.
  55. Furukawa, Y., & Ponce, J. (2010). Accurate, dense, and robust multiview stereopsis. IEEE transactions on pattern analysis and machine intelligence, 32(8), 1362-1376.
  56. Habib, A. F., Kim, E. M., & Kim, C. J. (2007). New methodologies for true orthophoto generation. Photogrammetric Engineering & Remote Sensing, 73(1), 25-36.
  57. Hirschmuller, H. (2005, June). Accurate and efficient stereo processing by semi-global matching and mutual information. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on (Vol. 2, pp. 807-814). IEEE.
  58. Hu, J., You, S., Neumann, U., & Park, K. K. (2004, May). Building modeling from LiDAR and aerial imagery. In ASPRS (Vol. 4, pp. 23-28).
  59. Kim, Z., Huertas, A., & Nevatia, R. (2001). Automatic description of buildings with complex rooftops from multiple images. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on (Vol. 2, pp. II-II). IEEE.
  60. Maini, R., & Aggarwal, H. (2009). Study and comparison of various image edge detection techniques. International journal of image processing (IJIP), 3(1), 1-11.
  61. Naoum, S., & Tsanis, I. K. (2004). Ranking spatial interpolation techniques using a GIS-based DSS. Global Nest, 6(1), 1-20.
  62. Ngo, T. T., Collet, C., & Mazet, V. (2015,). Automatic rectangular building detection from VHR aerial imagery using shadow and image segmentation. In Image Processing (ICIP), 2015 IEEE International Conference on (pp. 1483-1487). IEEE.
  63. Nielsen, M. Ø. (2004). True orthophoto generation (Master's thesis, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark).
  64. Oda, K., Lu, W., Uchida, O. and Doihara, T., 2004. “Triangle-based Visibility Analysis and True Orthoimage Generation”. Int. Arch. Photogrammetry, Remote Sensing and Spatial Information, Vol.35 (3) pp.623-628.
  65. Ortner, M., Descombes, X., Zerubia, J., 2007. Building outline extraction from digital elevation models using marked point processes, International Journal of Computer Vision, 72(2), 107–132.
  66. Sampath, A. and Shan, J., 2007. Building boundary tracing and regularization from airborne lidar point clouds, Photogrammetric Engineering and Remote Sensing, 73(7): 805-812.
  67. San A, D. K. (2007). Automatic building extraction from high resolution stereo satellite images.
  68. Sun, S., & Savalggio, C. (2012,). Complex building roof detection and strict description from LiDAR data and orthorectified aerial imagery. In Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International (pp. 5466-5469). IEEE.
  69. Rafael, C. G., and Richard, E. W. (2002,). Digital Image Processing 2nd edition, Addison-Wesley, Tokyo, pp.555-574.
  70. Zhou, G., Chen, W., Kelmelis, J. A., & Zhang, D. (2005). A comprehensive study on urban true orthorectification. IEEE Transactions on Geoscience and Remote sensing, 43(9), 2138-2147.