Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 917-921, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-917-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
10 Jun 2016
A NOVEL SHIP DETECTION METHOD FOR LARGE-SCALE OPTICAL SATELLITE IMAGES BASED ON VISUAL LBP FEATURE AND VISUAL ATTENTION MODEL
Sui Haigang1 and Song Zhina2 1State Key Laboratory of Information Engineering In Surveying Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China
2Remote Sensing and Information Engineering. College of Wuhan University, Wuhan, 430079, China
Keywords: Ship Detection, Large-Scale, Optical Image, Visual LBP Feature, Visual Attention, Support Vector Machine (SVM) Abstract. Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.
Conference paper (PDF, 904 KB)


Citation: Haigang, S. and Zhina, S.: A NOVEL SHIP DETECTION METHOD FOR LARGE-SCALE OPTICAL SATELLITE IMAGES BASED ON VISUAL LBP FEATURE AND VISUAL ATTENTION MODEL, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 917-921, https://doi.org/10.5194/isprs-archives-XLI-B3-917-2016, 2016.

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