Abstract:
This paper presents a novel unified image fusion framework based on an application-adaptive importance measure. In the proposed framework, an important area is selected u...Show MoreMetadata
Abstract:
This paper presents a novel unified image fusion framework based on an application-adaptive importance measure. In the proposed framework, an important area is selected using the importance measure obtained for each image type in each application. The key is to learn this application-adaptive importance measure that can select the important area irrespective of the input image type without manually designing the algorithm for each application. Then, the fused intensity is generated using Poisson image reconstruction. Experimental results demonstrate that the proposed framework is effective for various applications including depth-perceptible image enhancement, temperature-preserving image fusion, and haze removal.
Published in: IEEE Transactions on Computational Imaging ( Volume: 5, Issue: 1, March 2019)