一种基于目标区域知识提取地面目标显著性的新方法

W. Hao, Wei Haiping, Zhang Bochuan
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引用次数: 0

摘要

提出了一种基于目标区域知识,结合生物视觉机制的兴趣区域提取算法。该算法根据对目标的了解,采用横向抑制滤波对图像进行预处理。然后利用结构模式建立目标的显著性模型。该算法避免了像素及其局部邻域的高维特征计算,大大提高了运算速度。此外,通过目标区域知识构建的显著性模型比传统的自顶向下显著性计算具有更高的性能和可靠性。
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A novel method for extracting saliency of ground target based on the knowledge of target region
A novel interest region extraction algorithm is proposed, which is based on the knowledge of target region, combined with biological vision mechanism. Depending on the knowledge of target, the algorithm preprocesses the image by applying lateral inhibition filter. Then build the saliency model of target by using structural pattern. The algorithm avoids high-dimension features calculation of pixel and its local neighborhood, therefore greatly enhances the operational speed. Otherwise, the saliency model built through target region knowledge has higher performance and is more reliable than the traditional top-down saliency calculation.
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