Perception-based seam cutting for image stitching
Perception-based seam cutting for image stitching
复制标题
基于感知的图像拼接接缝
DOI：
10.1007/s11760-018-1241-9
复制
发表时间：
2018-07-01
影响因子：
2.3
通讯作者：
Wang, Chao
中科院分区：
文献类型：
--
作者：
Li, Nan;Liao, Tianli;Wang, Chao
由于不完美的图像捕获，图像拼接在消费级摄影中仍然具有挑战性。最近的工作表明，缝切割方法可以有效地减轻局部错位产生的伪影。通常，接缝切割方法是根据能量最小化来描述的。然而，现有的方法很少考虑人类的感知在其能量函数，这有时会导致存在另一个缝，这是感知优于具有最小能量的一个。在本文中，我们提出了一种新的基于感知的接缝切割方法，考虑到人类感知的非线性和不均匀性的能量最小化。我们的方法使用一个S形度量来表征感知的颜色歧视和显着性权重来模拟人眼倾向于更多地关注显着的物体。此外，我们的方法可以很容易地集成到其他拼接管道。有代表性的实验表明，传统的缝切割方法有很大的改进。
Image stitching is still challenging in consumer-level photography due to imperfect image captures. Recent works show that seam-cutting approaches can effectively relieve the artifacts generated by local misalignment. Normally, the seam-cutting approach is described in terms of energy minimization. However, few of existing methods consider the human perception in their energy functions, which sometimes causes that there exists another seam that is perceptually better than the one with the minimum energy. In this paper, we propose a novel perception-based seam-cutting approach that considers the nonlinearity and the nonuniformity of human perception into the energy minimization. Our method uses a sigmoid metric to characterize the perception of color discrimination and a saliency weight to simulate that the human eye inclines to pay more attention to the salient objects. In addition, our approach can be easily integrated into other stitching pipelines. Representative experiments demonstrate substantial improvements over the conventional seam-cutting approach.