• DocumentCode
    36167
  • Title

    Local Edge Distributions for Detection of Salient Structure Textures and Objects

  • Author

    Xiangyun Hu ; Jiajie Shen ; Jie Shan ; Li Pan

  • Author_Institution
    Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China
  • Volume
    10
  • Issue
    3
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    466
  • Lastpage
    470
  • Abstract
    Automatic detection of regions of salient texture and objects is useful for analysis of remotely sensed imagery, such as for land cover classification, object detection, and change detection. Intuitively, the local edges on an image indicate spectral discontinuity and the existence of structure texture or objects. This letter explores a simple method for measuring the saliency of texture and objects based on the edge density and spatial evenness of the edge distribution in the local window of each pixel. This method generates a saliency map by computing the saliency index of each pixel. By segmenting the saliency map, the salient structure texture regions and the locations of objects can be extracted. The algorithm requires only the window size as the input parameter and is relatively simple to implement. Experiments using high-resolution images show its effectiveness and accuracy in the detection of salient structure texture regions, such as crops and residential areas, and man-made objects, such as airplanes, cars, etc.
  • Keywords
    geophysical image processing; geophysical techniques; image classification; image segmentation; remote sensing; change detection; high-resolution images; image indicate spectral discontinuity; land cover classification; local edge distributions; man-made objects; object detection; pixel local window; region automatic detection; remotely sensed imagery; saliency index; saliency map segmenting; salient structure textures; Airplanes; Feature extraction; Image edge detection; Image segmentation; Indexes; Object detection; Remote sensing; Edge distributions; object detection; saliency; structure texture;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2012.2210188
  • Filename
    6289342