基于视觉显著模型的遥感图像舰船快速检测

为了降低传统高分辨率海面遥感图像舰船目标检测方法的计算复杂度，提高检测速度，在舰船目标检测中引入了基于直方图对比度的视觉显著模型和空间降维算法，提出一种新的高分辨率海面遥感图像舰船目标快速检测算法。首先对高分辨率遥感图像进行空间降维，然后计算降维图的视觉显著图，突出感兴趣目标区域，最后利用最大类间方差法分割视觉显著图以获取舰船目标候选区域。结果表明，目标检测所消耗的时间减小为原来的10%~12%，弱化了复杂海面纹理背景对目标检测的影响。该研究提高了高分辨率遥感图像舰船目标的检测效率。

Rapid ship detection in remote sensing images based on visual saliency model

In order to reduce the computational complexity of ship target detection methods for sea surface remote sensing images of traditional high resolution and improve the speed of detection, combined with visual salience algorithm based on histogram contrast and spatial dimension reduction algorithm, a new ship target fast detection algorithm for sea surface remote sensing images of high resolution was proposed.Firstly, spatial dimension reduction of high resolution remote sensing images was carried out. The saliency map was calculated and the interest area of the target area was highlighted. At last, the visual salient image was segmented by the method of maximum inter class variance to obtain the candidate region of the ship target. The results show that the time consumed by the target detection is reduced to 10%~12% of the original.The influence of complex sea surface texture background on target detection is weakened.The research improves ship target detection efficiency for high resolution remote sensing images.