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Fast calibration stitching algorithm for underwater camera
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DOI：10.1007/s11042-023-14533-8.png)
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摘要
En 中文
Underwater environment is complex and changeable. In order to obtain more underwater environment information. The larger the field of view of underwater images collected by ROV, the more information is contained. Effective methods to obtain large field of view include fish-eye lens and image stitching. In order to obtain larger field information, we combine the two methods and propose a splicing algorithm that can be applied to fish-eye lenses. This algorithm includes two parts, the first part is correction the fish-eye images, on the basis of the traditional chessboard correction method to improve, this paper put forward a new adaptive gray level method, this method can keep more angular point features, can be more accurate extraction of checkerboard angular point, will be further accurate correction result. In order to achieve real-time underwater patchwork effect. For stitching the corrected images, this paper proposes a fast stitching algorithm (FASTITCH), in the process of image stitching, the algorithm can preserve image feature points and transposed matrix of image matching, so as to calculate the new coordinates, joining together the original feature points in the image. Using this coordinate to match the feature points of another image can save the time of finding feature points in the stitching image, and finally speed up the stitching and complete the task of real-time stitching. The experiment proves that: The error obtained by the new correction method is smaller. Compared with the traditional feature point stitching algorithm, the fast stitching algorithm (FASTITCN) proposed in this paper can shorten the stitching time by about 20%.
Keyword:
Fish-eye correction
Adaptive grayscale conversion method
FASTITCH stitch algorithm
Fish-eye stitching
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
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