TY - GEN
T1 - Infrared and Visible Image Fusion based on Log-domain Decomposition and Information Interaction
AU - Fei, Erfang
AU - Zhou, Zhiqiang
AU - Yang, Rao
AU - Miao, Lingjuan
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/10/21
Y1 - 2022/10/21
N2 - In order to better preserve the salient targets and detail information of the infrared and visible images, a novel image fusion method based on log-domain decomposition and information interaction is proposed in this paper. Specifically, the infrared and visible images are first transformed into the logarithmic domain for a two-scale decomposition, which helps to extract more high-contrast information compared to decomposing them directly in image space. A visual saliency strategy is then used to fuse the base layer images. As to detail layers, a combined local visual saliency and detail preservation strategy is proposed to determine the final fusion weights. In addition, it is worth noting that the visible image information is introduced into the infrared detail layer before fusion, which achieves the information complementation and interaction of two source images. The experiment results demonstrate that the proposed method outperforms other fusion methods in both qualitative and quantitative assessments.
AB - In order to better preserve the salient targets and detail information of the infrared and visible images, a novel image fusion method based on log-domain decomposition and information interaction is proposed in this paper. Specifically, the infrared and visible images are first transformed into the logarithmic domain for a two-scale decomposition, which helps to extract more high-contrast information compared to decomposing them directly in image space. A visual saliency strategy is then used to fuse the base layer images. As to detail layers, a combined local visual saliency and detail preservation strategy is proposed to determine the final fusion weights. In addition, it is worth noting that the visible image information is introduced into the infrared detail layer before fusion, which achieves the information complementation and interaction of two source images. The experiment results demonstrate that the proposed method outperforms other fusion methods in both qualitative and quantitative assessments.
KW - image fusion
KW - information interaction
KW - log-domain decomposition
KW - visual saliency
UR - http://www.scopus.com/inward/record.url?scp=85145556334&partnerID=8YFLogxK
U2 - 10.1145/3569966.3570047
DO - 10.1145/3569966.3570047
M3 - Conference contribution
AN - SCOPUS:85145556334
T3 - ACM International Conference Proceeding Series
SP - 243
EP - 247
BT - CSSE 2022 - 2022 5th International Conference on Computer Science and Software Engineering
PB - Association for Computing Machinery
T2 - 5th International Conference on Computer Science and Software Engineering, CSSE 2022
Y2 - 21 October 2022 through 23 October 2022
ER -