期刊
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
卷 52, 期 8, 页码 4511-4523出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2013.2282355
关键词
Circle frequency-histograms of oriented gradients (CF-HOG) feature; optical panchromatic image analysis; Reed-Xiaoli algorithm; ship detection
类别
资金
- National Natural Science Foundation of China [61273245, 91120301]
- 973 Program [2010CB327904]
- State Key Laboratory of Virtual Reality Technology and Systems, Beihang University [BUAA-VR-12KF-07]
- Program for New Century Excellent Talents in University of the Ministry of Education of China [NCET-11-0775]
- Beijing Key Laboratory of Digital Media, Beihang University, Beijing, P.R. China
Ship detection in high-resolution optical imagery is a challenging task due to the variable appearances of ships and background. This paper aims at further investigating this problem and presents an approach to detect ships in a coarse-to-fine manner. First, to increase the separability between ships and background, we concentrate on the pixels in the vicinities of ships. We rearrange the spatially adjacent pixels into a vector, transforming the panchromatic image into a fake hyperspectral form. Through this procedure, each produced vector is endowed with some contextual information, which amplifies the separability between ships and background. Afterward, for the fake hyperspectral image, a hyperspectral algorithm is applied to extract ship candidates preliminarily and quickly by regarding ships as anomalies. Finally, to validate real ships out of ship candidates, an extra feature is provided with histograms of oriented gradients (HOGs) to generate a hypothesis using AdaBoost algorithm. This extra feature focuses on the gray values rather than the gradients of an image and includes some information generated by very near but not closely adjacent pixels, which can reinforce HOG to some degree. Experimental results on real database indicate that the hyperspectral algorithm is robust, even for the ships with low contrast. In addition, in terms of the shape of ships, the extended HOG feature turns out to be better than HOG itself as well as some other features such as local binary pattern.
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