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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Region-of-Interest Extraction Based on Frequency Domain Analysis and Salient Region Detection for Remote Sensing Image
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Region-of-Interest Extraction Based on Frequency Domain Analysis and Salient Region Detection for Remote Sensing Image

机译:基于频域分析和显着区域检测的遥感图像兴趣区域提取

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摘要

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.
机译:用于检测遥感图像中视觉上显着区域或目标的传统方法是不准确的,并且计算复杂。在这封信中,提出了一种基于频域分析和显着区域检测(FDA-SRD)的快速,有效的感兴趣区域提取方法。首先,使用HSI变换对从RGB空间到HSI空间的遥感图像进行预处理。其次,采用基于四元数傅里叶变换的频域分析策略快速生成显着图。最后,通过基于高斯金字塔的自适应阈值分割算法来描述显着区域。与现有模型相比,新算法的计算效率更高,并且提供了更直观的检测结果。

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