基于改进相位相关与特征点配准的多图拼接算法

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。

Multi-images Mosaic Algorithm Based on Improved Phase Correlation and Feature Point Registration

The result of image mosaic suffers from different exposure of the camera,scale change,rotation,ambient noise and light interference.Manual sorting images have problems of high error rate and poor efficiency.In this paper,a new algorithm of multi-images mosaic based on improved phase correlation and feature point registration was proposed.Firstly,the improved phase correlation algorithm based on log polar transformation is used to calculate parameters of scaling,rotation and translation.Sort rules are made according to the peak size of impulse function energy.Then,the Harris corner points are extracted in overlapping positions,the matching point pairs are purified by the improved Ransac algorithm,and the transformation matrix is optimized to complete mosaic .At last,according to the phenomenon of joint,images are processed by NSCT transform algorithm to decompose low frequency and high frequency sub-bands.The new fusion strategy can make the image joint seem smooth and natural.The results of the experiments confirm that the model parameters established by the new algorithm are accurate and efficient,and the mosaic has high robustness to complex environment and chaotic sequence images.