Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Dim point target detection is of great importance in both civil and military fields.  a novel spatiotemporal filter is proposed to incorporate both the spatial and temporal features ofmoving dim point targets. Since targets are expected to be detected as far as possible, in this situation, they have no texture features in spatial dimensions, appearing like isolated points. Based on the attributes, potential targets are extracted by searching the local maximum point in a sliding window. And the potential targets are then correlated based on target moving patterns. After combining local maximum points and target moving patterns, structure background in infrared scene is removed. Next, the temporal profiles of infrared sense are revied and examined. By a new max-median filter performing on temporal profiles, the intensity of target pulse signal is extracted. Finally, each temporal profile is divided into several pieces to estimate the variance of the temporal profiles, which leads to a new detection metric. The proposed approach is tested via several infrared image sequences. The results show that our proposed method can significantly reduce the complex background in aerial infrared image sequence and have a good detection performance.
['Zhaohui Li', 'Xiaorui Wang', 'Jianqi Zhang', 'Delian Liu']
I am writing a research paper on a idea Novel spatiotemporal filter for dim point targets detection in infrared image sequences
[{"from": "human", "value": "I am writing a research paper on a idea Novel spatiotemporal filter for dim point targets detection in infrared image sequences"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Dim point target detection is of great importance in both civil and military fields.  a novel spatiotemporal filter is proposed to incorporate both the spatial and temporal features ofmoving dim point targets. Since targets are expected to be detected as far as possible, in this situation, they have no texture features in spatial dimensions, appearing like isolated points. Based on the attributes, potential targets are extracted by searching the local maximum point in a sliding window. And the potential targets are then correlated based on target moving patterns. After combining local maximum points and target moving patterns, structure background in infrared scene is removed. Next, the temporal profiles of infrared sense are revied and examined. By a new max-median filter performing on temporal profiles, the intensity of target pulse signal is extracted. Finally, each temporal profile is divided into several pieces to estimate the variance of the temporal profiles, which leads to a new detection metric. The proposed approach is tested via several infrared image sequences. The results show that our proposed method can significantly reduce the complex background in aerial infrared image sequence and have a good detection performance."}]