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  • 1. Ronggui, Ma
    et al.
    Weixing, Wang
    KTH.
    Sheng, Liu
    Extracting roads based on Retinex and improved Canny operator with shape criteria in vague and unevenly illuminated aerial images2012In: Journal of Applied Remote Sensing, ISSN 1931-3195, E-ISSN 1931-3195, Vol. 6, 063610- p.Article in journal (Refereed)
    Abstract [en]

    An automatic road extraction method for vague aerial images is proposed in this paper. First, a high-resolution but low-contrast image is enhanced by using a Retinex-based algorithm. Then, the enhanced image is segmented with an improved Canny edge detection operator that can automatically threshold the image into a binary edge image. Subsequently, the linear and curved road segments are regulated by the Hough line transform and extracted based on several thresholds of road size and shapes, in which a number of morphological operators are used such as thinning (skeleton), junction detection, and endpoint detection. In experiments, a number of vague aerial images with bad uniformity are selected for testing. Similarity and discontinuation-based algorithms, such as Otsu thresholding, merge and split, edge detection-based algorithms, and the graph-based algorithm are compared with the new method. The experiment and comparison results show that the studied method can enhance vague, low-contrast, and unevenly illuminated color aerial road images; it can detect most road edges with fewer disturb elements and trace roads with good quality. The method in this study is promising.

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