title: A total variation-based algorithm for pixel-level image fusion.
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.
authors.forename: Mrityunjay
authors.initials: M
authors.lastname: Kumar
authors.forename: Sarat
authors.initials: S
authors.lastname: Dass
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging; D016208:Databases, Factual; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D008279:Magnetic Resonance Imaging; D008962:Models, Theoretical; D025341:Principal Component Analysis; D011877:Radionuclide Imaging; D014057:Tomography, X-Ray Computed