Abstract-In this paper, a total variation (TV) based approach is proposed for pixel-level fusion to fuse images acquired using multiple sensors. In this approach, fusion is posed as an inverse problem and a locally affine model is used as the forward model. A TV seminorm based approach in conjunction with principal component analysis is used iteratively to estimate the fused image. The feasibility of the proposed algorithm is demonstrated on images from computed tomography (CT) and magnetic resonance imaging (MRI) as well as visible-band and infrared sensors. The results clearly indicate the feasibility of the proposed approach. Index Terms-Eigenvector, forward model, image fusion, inverse problem, pixel-level fusion, total variation (TV).
Kumar and Dass REF proposed a pixel-level fusion technique using the total variation-based approach together with a principal component analysis technique.
A Total Variation-Based Algorithm for Pixel-Level Image Fusion
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Mathematics Computer Science Medicine