Directional morphological image transforms for lineament extraction from remotely sensed images

被引:35
|
作者
Tripathi, NK [1 ]
Gokhale, KVGK
Siddiqui, MU
机构
[1] Indian Inst Technol, Dept Civil Engn, Kanpur 208016, Uttar Pradesh, India
[2] Indian Inst Technol, Dept Elect Engn, Kanpur 208016, Uttar Pradesh, India
关键词
D O I
10.1080/014311600750019895
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Morphological image transforms find their basis in the notions of mathematical morphology. An attempt is made to develop morphological transforms for enhancement of directional edges and lineaments from satellite imagery. Geostructural features are generally oriented in preferred directions. This information has been utilized in designing structuring elements for morphological transforms. Several shapes and sizes of structuring elements have been designed and applied to delineate lineaments in different litho-environments of the same study area. Top hat transform has been applied using the directional structuring elements for edge image at 0 degrees, 30 degrees, 60 degrees, 90 degrees, 120 degrees and 150 degrees. Geological lineaments such as faults could be easily identified on an edge image obtained using top hat transformation followed by an image superimposition technique. The lineament map was developed using directionally enhanced edge images and the results have been verified.
引用
收藏
页码:3281 / 3292
页数:12
相关论文
共 50 条
  • [1] Efficient implementation of morphological index for building/shadow extraction from remotely sensed images
    Ignacio Jimenez, Luis
    Plaza, Javier
    Plaza, Antonio
    JOURNAL OF SUPERCOMPUTING, 2017, 73 (01): : 482 - 494
  • [2] Efficient implementation of morphological index for building/shadow extraction from remotely sensed images
    Luis Ignacio Jiménez
    Javier Plaza
    Antonio Plaza
    The Journal of Supercomputing, 2017, 73 : 482 - 494
  • [3] Fast Road Network Extraction from Remotely Sensed Images
    Krylov, Vladimir A.
    Nelson, James D. B.
    ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2013, 2013, 8192 : 227 - 237
  • [4] A Gibbs point process for road extraction from remotely sensed images
    Stoica, R
    Descombes, X
    Zerubia, J
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2004, 57 (02) : 121 - 136
  • [5] Building Extraction from Remotely Sensed Images by Integrating Saliency Cue
    Li, Er
    Xu, Shibiao
    Meng, Weiliang
    Zhang, Xiaopeng
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (03) : 906 - 919
  • [6] Support Vector Machines for road extraction from remotely sensed images
    Yager, N
    Sowmya, A
    COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS, 2003, 2756 : 285 - 292
  • [7] A Gibbs Point Process for Road Extraction from Remotely Sensed Images
    Radu Stoica
    Xavier Descombes
    Josiane Zerubia
    International Journal of Computer Vision, 2004, 57 : 121 - 136
  • [8] Hierarchical extraction of landslides from multiresolution remotely sensed optical images
    Kurtz, Camille
    Stumpf, Andre
    Malet, Jean-Philippe
    Gancarski, Pierre
    Puissant, Anne
    Passat, Nicolas
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2014, 87 : 122 - 136
  • [9] Superresolution of Noisy Remotely Sensed Images Through Directional Representations
    Czaja, Wojciech
    Murphy, James M.
    Weinberg, Daniel
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2018, 15 (12) : 1837 - 1841
  • [10] Automatic Channel Network Extraction From Remotely Sensed Images by Singularity Analysis
    Isikdogan, Furkan
    Bovik, Alan
    Passalacqua, Paola
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2015, 12 (11) : 2218 - 2221