频域分析在遥感图像显著区域检测时可以很好地检测到显著区域的边缘部分，但是，往往在显著区域的内部产生误检测。提出了一种基于图像高频信息多尺度融合的视觉显著区域检测算法，将遥感图像进行多尺度的高斯金字塔分解，对分解后的每一级图像进行傅里叶变换，提取变换后的高频信息进行多尺度融合，获得最终显著图。结合该显著图提取遥感影像视觉显著区域不仅能够有效排除显著区域内部误检测问题，而且获得了更为精确的显著区域细节。此外，该算法较Itti模型具有更低计算复杂度。

Frequency domain analysis can well detect the edge of the salient region in the remote sensing imagery detecting. But it may mistakenly regard the inner parts of the saliency region as the background. A new algorithm based on multi-scale fusion techniques of the image high frequency information is proposed. First, the new algorithm creates several spatial scales of remote sensing images by using Gaussian pyramid. Then, for each scale, the new algorithm can get the high frequency information by the Fourier transform. Finally, the new algorithm gets the final saliency map by fusing the high frequency information on one scale. The new algorithm can not only well extract details of the salient region, but also effectively get rid of mistaken detection of the inner parts of the saliency region. Comparing with Itti model, the new algorithm has lower computation complexity.