传统高分辨率遥感影像感兴趣区域的检测方法通常要利用先验知识库对整幅影像进行全局分析与搜索，具有很高计算复杂度。从人眼视觉特性出发，提出一种新的高分辨率遥感影像感兴趣区域快速检测算法。基于视觉关注模型对高分辨率遥感影像进行空间降维，确定视觉关注焦点；根据关注焦点位置在原始遥感影像中描述出相应的感兴趣区域。实验结果表明，新方法不仅具有较低计算复杂度，而且有效避免了影像分割、特征检测等计算复杂度较高的全图搜索方法，提高了高分辨率遥感影像感兴趣区域的检测效率。

The traditional detection methods for these regions of interest in high resolution remote sensing image generally search the whole image on the basis of prior knowledge, which leads to high computational complexity. A new fast detection algorithm based on human visual characteristic for these regions of interest in high resolution remote sensing image is proposed. The new algorithm based on visual attention model applies spatial dimension reduction strategy to confirm these focuses of visual attention. According to the positions of focuses of visual attention, the new algorithm describes these relevant regions of interest in the original remote sensing image. The experimental results show that the new algorithm could not only have the lower computational complexity, but also avoid image segmentation and feature detection for the whole image and improve the detection efficiency of regions of interest in high resolution remote sensing image.