Remote sensing image ship target detection method based on visual attention model

Yuejiao Sun; Wuhu Lei; Xiaodong Ren

doi:10.1117/12.2296260

15 November 2017 Remote sensing image ship target detection method based on visual attention model

Yuejiao Sun, Wuhu Lei, Xiaodong Ren

Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 106053Z (2017) https://doi.org/10.1117/12.2296260
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China

Abstract

The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

Citation Download Citation

Yuejiao Sun, Wuhu Lei, and Xiaodong Ren "Remote sensing image ship target detection method based on visual attention model", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 106053Z (15 November 2017); https://doi.org/10.1117/12.2296260

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