Region-of-Interest Extraction Based on Frequency Domain Analysis and Salient Region Detection for Remote Sensing Image
Region-of-Interest Extraction Based on Frequency Domain Analysis and Salient Region Detection for Remote Sensing Image
复制标题
基于频域分析和显着区域检测的遥感图像感兴趣区域提取
DOI：
10.1109/lgrs.2013.2281827
复制
发表时间：
2014-05-01
影响因子：
4.8
通讯作者：
Yang, Kaina
中科院分区：
文献类型：
--
作者：
Zhang, Libao;Yang, Kaina
传统的方法用于检测视觉显著区域或目标在遥感图像中是不准确的，并且计算复杂。本文提出了一种基于频域分析和显著区域检测的快速、有效的感兴趣区域提取方法。首先，利用HSI变换对遥感图像进行从RGB空间到HSI空间的预处理;其次，采用基于四元数傅立叶变换的频域分析策略快速生成显著图。最后，采用基于高斯金字塔的自适应阈值分割算法描述显著区域。与现有的模型相比，新算法在计算上更有效，并提供更准确的视觉检测结果。
Traditional approaches for detecting visually salient regions or targets in remote sensing images are inaccurate and prohibitively computationally complex. In this letter, a fast, efficient region-of-interest extraction method based on frequency domain analysis and salient region detection (FDA-SRD) is proposed. First, the HSI transform is used to preprocess the remote sensing image from RGB space to HSI space. Second, a frequency domain analysis strategy based on quaternion Fourier transform was employed to rapidly generate the saliency map. Finally, the salient regions are described by an adaptive threshold segmentation algorithm based on Gaussian Pyramids. Compared with existing models, the new algorithm is computationally more efficient and provides more visually accurate detection results.