Orientation-coherence-feature-based Method to Detect Small Target in Drift-scanning Image
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摘要: 提出一种基于方向一致性特征的小目标检测方法, 对漂移扫描星图中的小目标进行检测. 首先,根据小目标的一般描述, 建立特征模型对小目标区域进行表示; 其次,分析Gabor滤波器工作机理, 构造了主次两组四个方向通道的滤波器,对研究对象进行特征提取, 并以一致性描述指标对目标特征定量刻画; 最后,依据特征描述模型, 给出了小目标的检测算子及相应参数的选择依据. 对实际星图的实验结果表明,本文方法在小目标检测和高频干扰目标抑制上具有很好的效果,验证了本文所建模型的合理性.Abstract: In order to detect the small target in the drift-scanning image, this paper proposes a method based on orientation coherence features. According to the general description about small target, a feature model is established to represent the region of small target firstly. By the analysis of Gabor filter, the primary and secondary filter groups with four orientation channels are then constructed to extract the features of objects. And a consistency description indicator is used for measuring the feature quantitatively. Finally, the small target detection operator and the corresponding parameter selection principle are given by the feature description model. Experiments on an actual image have shown that the method proposed in this paper has good performance on target detection and high-frequency interference suppression. And the model proposed is testified to be reasonable.
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Key words:
- Signal processing /
- target detection operator /
- feature model /
- orientation coherence /
- drift-scanning
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