A Dim Small Target Detection Method Based On Spatial-Frequency Domain Features Space

The target detection, especially extracting low SNR potential targets and stars from the star images, plays as a key technology in the space debris surveillance. Due to the complexity of the imaging environment, the detection of dim small targets in star images faces many difficulties, including low SNR and rare unstable features. This paper proposes a dim small target detection method based on the high dimensional spatial-frequency domain features extracted by filter bank, and training the support vector machine (SVM) classifier. The experimental results demonstrate that the proposed method exceeds the state-of-the-art on the ability to detect low SNR targets.