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Image Edge Detection for Stitching Aerial Images with Geometrical Rectification

机译:用几何整流拼接空中图像的图像边缘检测

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Changes of the flight attitude of unmanned aircraft cause nonlinear distortion in the aerial images. Stitching these images without geometric rectification may cause the problem of mismatching. However, the geometric rectification model produces invalid regions at the edge of images. A direct cutting for these invalid regions leads to removing lots of useful information, whereas a noisy seam is visible in the stitched image if the edge cutting is omitted. We propose a solution of edge detection for detecting invalid and noisy regions. More precisely, our method includes two passes of edge detection for images with geometric rectification. The first pass of image edge detection is to find the boundary between valid and invalid scenes. The second pass is to detect the noisy regions. The invalid and noisy regions are finally removed for image stitching, and the effective areas of the image are kept to the maximum extent. Experimental results demonstrate the efficacy of the proposed method.
机译:无人驾驶飞机飞行态度的变化导致航空图像中的非线性变形。没有几何整流缝合这些图像可能导致错配的问题。然而,几何整流模型在图像的边缘产生无效区域。这些无效区域的直接切割导致删除许多有用信息,而如果省略了边缘切割,则在缝合图像中可见噪声。我们提出了用于检测无效和嘈杂区域的边缘检测解决方案。更确切地说,我们的方法包括用于具有几何整流的图像的两个边沿检测通行证。图像边缘检测的第一次通过是找到有效和无效场景之间的边界。第二次通过是检测嘈杂的区域。对于图像拼接,最终删除了无效和嘈杂的区域,并且将图像的有效区域保持在最大程度。实验结果表明了该方法的功效。

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