Using planar stitching algorithm causes serious distortions in the panorama image

thereby resulting in difficulty ensuring good visual consistency. Meanwhile

the traditional cylindrical stitching algorithm cannot meet real-time requirements. To overcome these shortcomings

this paper proposes a cylindrical panorama stitching algorithm based on the improved SIFT (scale-invariant feature transform) feature descriptor. First

the image sequences to be stitched are transformed using cylindrical projection

and then the improved SIFT feature detector is adopted to extract the feature points. Accordingly

64 dimensional SIFT feature descriptors are generated. Based on the Euclidean distance of feature descriptors

the initial feature points are determined. By using RANSAC (random sample consensus) method

false matching feature points can be eliminated further and the space transformation matrix between the images to be stitched can be constructed. Finally

the image registration can be completed successfully according to the above-mentioned space transformation matrix

where the weighted average fusion method is used to realize the seamless splicing of images. This paper presents a new cylindrical image-stitching algorithm

which can effectively avoid distortion problems in planar stitching algorithm. The proposed algorithm achieves good visual consistency of panoramic image. The speed of the proposed algorithm is nearly two times of that of the traditional cylindrical image-stitching algorithm. As obtained from the experiment on panorama images using image sequences with different numbers and sizes

the proposed algorithm can stitch images more quickly and more efficiently than the planar stitching algorithm and the traditional cylindrical stitching algorithm. The generated panorama image has wide vision and high resolution

and is suitable for image-stitching applications of real-time requirements.