A new optimal seam selection method for airborne image stitching

H. Gu, Yue Yu, Weidong Sun
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引用次数: 15

Abstract

Image stitching techniques are widely used to integrate multi-view or sequential images into one image. But visible seams, blurring, or ghosting effects may occur in the overlapping regions for real image stitching. One approach to solve this problem is to find some kinds of seams in regions where the images agree, and then a weighted or blended integrating can be carried out around the pixels on the seams, which makes the transitions from one image to the other not visible. The traditional dynamic programming based method is proved to be effective to find such optimal seam but has an obvious drawback that its searching direction is restricted, so that it is not suitable to find an optimal seam connecting two specified points which is often required for sequential image stitching. Facing the above problem, a new optimal seam definition based on minimum cost is given, and then an optimal seam selection method based on enhanced dynamic programming is proposed in this paper. The analysis and visual results of our experiments using some real airborne sequential images show that, the approach proposed in this paper can handle significant structure misalignment and eliminates structure seam for the global seamless image stitching.
一种新的航空图像拼接最优缝选择方法
图像拼接技术被广泛用于将多视图或连续图像整合成一幅图像。但是,在实际图像拼接的重叠区域可能会出现可见的接缝、模糊或重影效果。解决这一问题的一种方法是在图像一致的区域找到某些类型的接缝,然后在接缝上的像素周围进行加权或混合积分,这使得从一张图像到另一张图像的过渡不可见。传统的基于动态规划的方法可以有效地找到这类最优缝,但其缺点是搜索方向受限,不适合寻找序列图像拼接中经常需要的连接两个指定点的最优缝。针对上述问题,给出了一种新的基于最小代价的最优煤层定义,并在此基础上提出了一种基于增强动态规划的最优煤层选择方法。实际机载序列图像的实验分析和视觉结果表明,本文所提出的方法能够有效地处理明显的结构错位,消除结构缝,实现图像的全局无缝拼接。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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