Authors:
Chengming Zou
;
Pei Wu
and
Zeqian Xu
Affiliation:
Wuhan University of Technology, China
Keyword(s):
Image Extraction, Image Stitching, Collaborative Calibration, Multi-band Blending.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Classification
;
Computer Vision, Visualization and Computer Graphics
;
Feature Selection and Extraction
;
Geometry and Modeling
;
Image-Based Modeling
;
Pattern Recognition
;
Software Engineering
;
Theory and Methods
Abstract:
Considering the slow speed of panorama image stitching and the ghosting of traditional image stitching
algorithms, we propose a solution by improving the classical image stitching algorithm. Firstly, a SIFT
algorithm based on block matching is used for feature matching which was proposed in our previously
published paper. Then, the collaborative stitching of the color and depth cameras is applied to further enhance
the accuracy of image matching. Finally, according to a multi-band blending algorithm, we obtain a panoramic
image of high quality through image fusion. The proposed algorithm is based on two problems in the
technology of feature-based image stitching algorithm, the algorithm’s real-time and ghosting. A series of
experiments show that the accuracy and reliability of the improved algorithm have been increased. Besides a
comparison with AutoStitch algorithm illustrates the advantage of the improved algorithm in efficiency and
quality of stitching.