In this paper, we propose a task-oriented enhancing technique for extracting road networks from satellite images. By exploiting an approximate estimation of the potential road edges for guidance, we developed a joint enhancing filtering framework to generate a version of the input image that facilitates road network extraction. First, an adaptive smoothing scheme is designed to suppress the interference of noise or heavy textures, such as residential areas or terrain boundaries. By combining this scheme with the proposed novel anisotropic shock filter, the edges of the potential road regions can be kept sharp and clear. Through abundant experimental comparisons with state-of-the-art filtering techniques and quantitative evaluations using data from various satellite sensors, the performance of the proposed approach is comprehensively evaluated. The experimental results demonstrate that our system can address heavy high contrast textures and provide a meaningful improvement in the feature detection for road extraction.
['Yu Zang', 'Cheng Wang', 'Yao Yu', 'Lun Luo', 'Ke Yang', 'Jonathan Li']
Joint Enhancing Filtering for Road Network Extraction