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An Effective Method of Eliminating Ghosting in Image Mosaic

机译:一种消除图像马赛克重影的有效方法

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Image fusion method directly affects the stitching effect. If there are moving objects in the images, the same object may add together after fusion and cause ghosting. A fusion method which can effectively eliminate the exposure difference and ghosting is essential to image mosaic. The method of optimal seam can eliminate integrated ghosting. But the optimal seam may include individual error points and its overall strength value is the smallest. The line is taken as the optimal seam incorrectly. So the ghosting may still exist. In order to avoid the impact of error points an improved optimal seam based on feature point is used in this paper. The scale invariant feature transform and the random sample consensus are used to ensure the detected feature points are accurate. The improved optimal seam do not regard the original optimal seam regards the point with smallest guidelines value as extended direction this paper regards the feature point as the extended direction. The feature point's strength value should have an appropriate weight value. It makes the optimal seam contain more feature points. In this way it can avoid the error points and dynamic elements. Both sides of the optimal seam have exposure differences, an image fusion method should be taken to achieve smooth and natural mosaic. Poisson fusion method can achieve the synthesis of the fragment. So Poisson fusion is used to eliminate exposure difference in this paper.
机译:图像融合方法直接影响拼接效果。如果在图像中存在移动对象,则相同的对象可以在融合后添加在一起并导致重影。一种能够有效消除曝光差和重影的融合方法对于图像马赛克至关重要。最佳接缝的方法可以消除集成重影。但最佳接缝可以包括单独的错误点,其总体强度值是最小的。该线被拍摄为不正确的最佳缝线。所以重影可能仍然存在。为了避免误差点的影响,本文使用了基于特征点的改进的最佳缝。规模不变特征变换和随机样本共识用于确保检测到的特征点是准确的。改进的最佳接缝不认为原始的最佳接缝,指导最小指导值的指示,因为延伸方向本文将特征点视为延伸方向。特征点的强度值应具有适当的重量值。它使最佳接缝包含更多特征点。以这种方式,它可以避免错误点和动态元素。最佳接缝的两侧具有曝光差异,应采取图像融合方法以实现光滑和自然的马赛克。泊松融合方法可以达到片段的合成。因此,泊松融合用于消除本文的曝光差异。

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