Title
An efficient method to build panoramic image mosaics
Abstract
This paper describes an efficient method to build panoramic image mosaics with multiple images. Conventional algorithms used geometrical feature points and optimization to compute the projective transformation, which is the relation between two consecutive images. However, building a panoramic image was very time consuming because of the iterative computation involved.The proposed method computed the projective transformation in overlapped areas of the two given images by using four seed points. The seed point is the highly textured point in the overlapped area of the reference image, which is extracted by using phase correlation. Because the region of interest (ROI) was restricted within overlapped areas of two images, more accurate correspondences were obtained. Before selecting the seed point, the histograms of the overlapped areas were equalized to mitigate the variation of the illumination conditions. After selecting the seed point, the weighted block matching algorithm (BMA) was used to minimize image distortion caused by camera rotation. An experiment was performed employing the proposed method with various images and the results were compared with peak signal to noise ratio (PSNR). Results showed that the proposed method built high-quality panoramic image mosaics in high speed.
Year
DOI
Venue
2003
10.1016/S0167-8655(03)00071-0
Pattern Recognition Letters
Keywords
Field
DocType
image distortion,panoramic image mosaics,panoramic image,overlapped area,projective transformation,multiple image,efficient method,panoramic image mosaic,high-quality panoramic image mosaic,consecutive image,projective transform,seed point,image warping,region of interest,peak signal to noise ratio,phase correlation,block matching algorithm
Histogram,Peak signal-to-noise ratio,Computer vision,Block-matching algorithm,Image warping,Pattern recognition,Homography,Artificial intelligence,Region of interest,Distortion,Phase correlation,Mathematics
Journal
Volume
Issue
ISSN
24
14
Pattern Recognition Letters
Citations 
PageRank 
References 
7
0.83
14
Authors
3
Name
Order
Citations
PageRank
Dae-Hyun Kim170.83
Yong-in Yoon2143.20
Jong-Soo Choi314730.10