摘要
We employ the target detection to improve the performance of the feature-based fusion of infrared and visible dynamic images, which forms a novel fusion scheme. First, the target detection is used to segment the source image sequences into target and background regions. Then, the dual-tree complex wavelet transform （DT-CWT） is proposed to decompose all the source image sequences. Different fusion rules are applied respectively in target and background regions to preserve the target information as much as possi-ble. Real world infrared and visible image sequences are used to validate the performance of the proposed novel scheme. Compared with the previous fusion approaches of image sequences, the improvements of shift invariance, temporal stability and consistency, and computation cost are all ensured.
We employ the target detection to improve the performance of the feature-based fusion of infrared and visible dynamic images, which forms a novel fusion scheme. First, the target detection is used to segment the source image sequences into target and background regions. Then, the dual-tree complex wavelet transform （DT-CWT） is proposed to decompose all the source image sequences. Different fusion rules are applied respectively in target and background regions to preserve the target information as much as possi-ble. Real world infrared and visible image sequences are used to validate the performance of the proposed novel scheme. Compared with the previous fusion approaches of image sequences, the improvements of shift invariance, temporal stability and consistency, and computation cost are all ensured.
基金
This work was jointly supported by the National Natural Science Foundation of China (No. 60375008)
the 2010 Shanghai EXPO Special Project of National Key Technologies R&D Program (No. 2004BA908B07)
the Shanghai-NRC International Co-operate Project (No. 05SN07118)
