计算机科学 ›› 2018, Vol. 45 ›› Issue (1): 313-319.doi: 10.11896/j.issn.1002-137X.2018.01.054
• 图形图像与模式识别 • 上一篇
厉丹,肖理庆,田隽,孙金萍
LI Dan, XIAO Li-qing, TIAN Jun and SUN Jin-ping
摘要： 针对拼接过程易受图像采集时曝光、尺度变化、旋转、环境噪声、光照等因素的影响,以及多图手动排序出错率高、耗时长等问题,提出了一种基于改进相位相关与特征点配准的多图拼接算法。首先,基于对数极坐标变换的改进相位相关算法来计算缩放、旋转和平移参数,根据冲激函数峰值实现多图自动排序；接着,在重叠位置提取Harris角点,改进的Ransac算法精确提纯匹配点对,优化变换矩阵以完成拼接；最后,通过利用NSCT变换算法多尺度分解低频、高频子带来制定融合策略,从而解决接缝明显的问题。实验结果表明,新算法 建立的模型参数准确且高效,拼接融合效果过渡自然,能较好地解决复杂环境及乱序图像的拼接问题。
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