Abstract
In this paper, an improved multi-exposure image fusion method for intelligent transportation systems (ITS) is proposed. Further, a new multi-exposure image dataset for traffic signs, TrafficSign, is presented to verify the method. In the intelligent transportation system, as a type of important road information, traffic signs are fused by this method to obtain a fused image with moderate brightness and intact information. By estimating the degree of retention of different features in the source image, the fusion results have adaptive characteristics similar to that of the source image. Considering the weather factor and environmental noise, the source image is preprocessed by bilateral filtering and dehazing algorithm. Further, this paper uses adaptive optimization to improve the quality of the output image of the fusion model. The qualitative and quantitative experiments on the new dataset show that the multi-exposure image fusion algorithm proposed in this paper is effective and practical in the ITS.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
