首页> 外文会议>International symposium on multispectral image processing and pattern recognition;MIPPR 2011 >A New Building Recognition Algorithm from High Resolution Remote Sensing Imagery
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A New Building Recognition Algorithm from High Resolution Remote Sensing Imagery

机译:高分辨率遥感影像的建筑物识别新算法

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The building recognition from high resolution remote sensing images is an internationally advanced research field. But there are still many difficult to be solved. In this paper, in order to extract and recognize the special building from the high resolution remote sensing images, a new algorithm is presented. First, a self-adaptive Average Absolute Difference Maximum edge enhancement algorithm is presented to enhance the edge of the building and suppress the background at one time. Second, the locally self-adaptive segmentation algorithm is implemented to obtain the binary image. Third, the thinning algorithm is implanted to obtain the single pixel edge of the building and a pruning algorithm is necessary in order to reduce the computation times in the following process. The following step is obtained by the Hough transformation to make the edge of the building into polygon. Finally, an Interior angle chain (LAC) is proposed to recognize the building with different shape. The experimental results demonstrate that the new algorithm can extract the special shape building quickly and accurately.
机译:高分辨率遥感影像对建筑物的识别是国际先进的研究领域。但是仍然有许多困难需要解决。为了提取和识别高分辨率遥感影像中的特殊建筑物,提出了一种新的算法。首先,提出了一种自适应平均绝对差最大边缘增强算法,以一次增强建筑物的边缘并抑制背景。其次,实现局部自适应分割算法以获得二值图像。第三,植入细化算法以获得建筑物的单个像素边缘,并且修剪算法是必需的,以便减少后续过程中的计算时间。通过霍夫变换将建筑物的边缘制成多边形,可以完成以下步骤。最后,提出了一个内部角度链(LAC)来识别具有不同形状的建筑物。实验结果表明,该新算法可以快速,准确地提取特殊形状的建筑物。

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