Fast Image Mosaicing Based on Histograms
Summary :
This paper introduces a fast image mosaicing technique that does not require costly search on image domain (e.g., pixel-to-pixel correspondence search on the image domain) and the iterative optimization (e.g., gradient-based optimization, iterative optimization, and random optimization) of geometric transformation parameter. The proposed technique is organized in a two-step manner. At both steps, histograms are fully utilized for high computational efficiency. At the first step, a histogram of pixel feature values is utilized to detect pairs of pixels with the same rare feature values as candidates of corresponding pixel pairs. At the second step, a histogram of transformation parameter values is utilized to determine the most reliable transformation parameter value. Experimental results showed that the proposed technique can provide reasonable mosaicing results in most cases with very feasible computations.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.11 pp.2701-2708
- Publication Date
- 2008/11/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.11.2701
- Type of Manuscript
- PAPER
- Category
- Image Processing and Video Processing
Authors
Keyword
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Akihiro MORI, Seiichi UCHIDA, "Fast Image Mosaicing Based on Histograms" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 11, pp. 2701-2708, November 2008, doi: 10.1093/ietisy/e91-d.11.2701.
Abstract: This paper introduces a fast image mosaicing technique that does not require costly search on image domain (e.g., pixel-to-pixel correspondence search on the image domain) and the iterative optimization (e.g., gradient-based optimization, iterative optimization, and random optimization) of geometric transformation parameter. The proposed technique is organized in a two-step manner. At both steps, histograms are fully utilized for high computational efficiency. At the first step, a histogram of pixel feature values is utilized to detect pairs of pixels with the same rare feature values as candidates of corresponding pixel pairs. At the second step, a histogram of transformation parameter values is utilized to determine the most reliable transformation parameter value. Experimental results showed that the proposed technique can provide reasonable mosaicing results in most cases with very feasible computations.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.11.2701/_p
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@ARTICLE{e91-d_11_2701,
author={Akihiro MORI, Seiichi UCHIDA, },
journal={IEICE TRANSACTIONS on Information},
title={Fast Image Mosaicing Based on Histograms},
year={2008},
volume={E91-D},
number={11},
pages={2701-2708},
abstract={This paper introduces a fast image mosaicing technique that does not require costly search on image domain (e.g., pixel-to-pixel correspondence search on the image domain) and the iterative optimization (e.g., gradient-based optimization, iterative optimization, and random optimization) of geometric transformation parameter. The proposed technique is organized in a two-step manner. At both steps, histograms are fully utilized for high computational efficiency. At the first step, a histogram of pixel feature values is utilized to detect pairs of pixels with the same rare feature values as candidates of corresponding pixel pairs. At the second step, a histogram of transformation parameter values is utilized to determine the most reliable transformation parameter value. Experimental results showed that the proposed technique can provide reasonable mosaicing results in most cases with very feasible computations.},
keywords={},
doi={10.1093/ietisy/e91-d.11.2701},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Fast Image Mosaicing Based on Histograms
T2 - IEICE TRANSACTIONS on Information
SP - 2701
EP - 2708
AU - Akihiro MORI
AU - Seiichi UCHIDA
PY - 2008
DO - 10.1093/ietisy/e91-d.11.2701
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2008
AB - This paper introduces a fast image mosaicing technique that does not require costly search on image domain (e.g., pixel-to-pixel correspondence search on the image domain) and the iterative optimization (e.g., gradient-based optimization, iterative optimization, and random optimization) of geometric transformation parameter. The proposed technique is organized in a two-step manner. At both steps, histograms are fully utilized for high computational efficiency. At the first step, a histogram of pixel feature values is utilized to detect pairs of pixels with the same rare feature values as candidates of corresponding pixel pairs. At the second step, a histogram of transformation parameter values is utilized to determine the most reliable transformation parameter value. Experimental results showed that the proposed technique can provide reasonable mosaicing results in most cases with very feasible computations.
ER -
English
