基于Harris与SIFT算法的自动图像拼接

图像拼接技术被广泛应用于遥感图像处理、计算机识别、医学图像分析及人工智能等方面。本文针对尺度不变特征变换(SIFT)算法特征提取较复杂、计算时间长的缺点,而Harris算法提取特征点快速有效的优点,提出了一种结合Harris与SIFT算法优点的算法,并将这种算法应用于图像的自动拼接。首先利用改进的Harris算法提取图像特征点,再使用SIFT算法来描述特征点,然后利用欧氏距离对所得的特征向量进行匹配,最终实现图像的自动拼接。实验结果表明,该方法能有效提高SIFT的匹配效率,较好地完成对图像的自动拼接。

The Automatic Image Mosaic Based on Harris and SIFT Algorithms

Image mosaic technology is widely used in many fields such as remote sensing image processing,computer recognition,medical image analysis and artificial intelligence,etc.Considering the shortcomings of scale-invariant feature transform(SIFT) algorithms,i.e.the complexity and time-consuming of the feature extraction actions,and the Harris algorithm can fast extract the features in the image,this paper presents an algorithm combining the advantages of the Harris and the SIFT and uses the algorithm in automatic image stitching.we firstly use the Harris algorithm to improve image feature extraction,secondly use the SIFT algorithm to describe the feature points,thirdly use the Euclidean distance to match the obtained feature vectors,and finally implement the automatic image stitching.Experimental results show that the method can effectively improve the efficiency of matching in the SIFT algorithm,and better do automatic image stitching.