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Traditional hyperspectral anomaly detection methods either model the global background or the local neighborhood, that bring some apparent drawbacks, such as the unreasonable assumption of uni-modular background in global detectors, or the high false alarms by sliding windows in local detectors. In this paper, a source component-based anomaly detection approach is proposed. It first extracts the source...
Feature points are low-level image features representing meaningful image regions and ideal candidates for feature-based image representation, and feature point detection is an essential pre-processing step for high-level computer vision tasks. Existing feature detection algorithms are either computationally intensive (multi-scale detectors) or sensitive to scale variations (single-scale detectors)...
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