An SIFT-Based Fast Image Alignment Algorithm for High-Resolution Image

Abstract

To solve the problem of high-resolution image alignment time overhead, an SIFT-based fast image alignment algorithm is presented. The overlap region of images is computed in detail by phase correlation algorithm to avoid a lot of useless calculations of non-overlapping region. After the distribution of feature points determined in difference of Gaussian through formula derivation, the total number of feature points is limited. The more stable spatially distributed for the feature points is obtained due to the expanded detection range of extreme points and added non-maximum suppression. It is noteworthy that the range of the descriptor is calculated by the method of down-sampling. And the circular descriptor is constructed with only 56-dimensional in the feature point descriptor generation stage, which makes the time of the descriptor generation and feature point matching shorter. This indicates that the total descriptor calculation is faster in lower dimensions by the new algorithm. In addition, experimental results show that the average time (9.60s, 13.46s, and 15.81s) of the proposed algorithm is 0.86%, 0.43%, and 0.10% of the SIFT algorithm, respectively. The overall speed is 2–3 orders of magnitude faster than the SIFT algorithm, which indicates that the new algorithm can solve the problem of high-resolution image alignment time overhead. The new algorithm provides a good stitching quality and shows an excellent performance for high-resolution image compared with several existing image stitching algorithms at the current. It indicates that the algorithm has potential application value in real-time image stitching.

Keywords

• Scale-invariant feature transform (SIFT)
• image alignment
• high-resolution image
• fast alignment