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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >Superpixel-Based Seamless Image Stitching for UAV Images
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Superpixel-Based Seamless Image Stitching for UAV Images

机译：基于Superpixel的无缝图像拼接为UAV图像

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摘要

Image stitching aims to generate a natural seamless high-resolution panoramic image free of distortions or artifacts as fast as possible. In this article, we propose a new seam cutting strategy based on superpixels for unmanned aerial vehicle (UAV) image stitching. Explicitly, we decompose the issue into three steps: image registration, seam cutting, and image blending. First, we employ adaptive as-natural-as-possible (AANAP) warps for registration, obtaining two aligned images in the same coordinate system. Then, we propose a novel superpixel-based energy function that integrates color difference, gradient difference, and texture complexity information to search a perceptually optimal seam located in continuous areas with high similarity. We apply the graph cut algorithm to solve the problem and thereby conceal artifacts in the overlapping area. Finally, we utilize a superpixel-based color blending approach to eliminate visible seams and achieve natural color transitions. Experimental results demonstrate that our method can effectively and efficiently realize seamless stitching, and is superior to several state-of-the-art methods in UAV image stitching.
机译：图像拼接旨在产生尽可能快的扭曲或伪影的自然无缝高分辨率全景图像。在本文中，我们提出了一种基于超像素的新型缝隙切割策略，用于无人驾驶飞行器（UAV）图像缝合。明确地，我们将问题分解为三个步骤：图像配准，接缝切割和图像混合。首先，我们采用自然的自然（AANAP）扭曲用于注册，在相同的坐标系中获得两个对齐的图像。然后，我们提出了一种基于精湛的超像素的能量函数，它集成了色差，梯度差和纹理复杂性信息，以搜索位于具有高相似性的连续区域的感知最佳接缝。我们应用了图形切割算法来解决问题，从而隐藏重叠区域中的伪像。最后，我们利用基于超像素的颜色混合方法来消除可见接缝并实现自然色转变。实验结果表明，我们的方法可以有效地有效地实现无缝缝合，并且优于UAV图像缝合中的几种最先进的方法。

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