Title :
A Total Variation-Based Algorithm for Pixel-Level Image Fusion
Author :
Kumar, Mrityunjay ; Dass, Sarat
Author_Institution :
Res. Labs., Eastman Kodak Co., Rochester, NY, USA
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 semi-norm 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.
Keywords :
computerised tomography; image fusion; image resolution; magnetic resonance imaging; principal component analysis; TV seminorm based approach; computed tomography; infrared sensor; magnetic resonance imaging; multiple sensors; pixel-level image fusion; principal component analysis; total variation-based algorithm; visible-band sensor; Eigenvector; forward model; image fusion; inverse problem; pixel-level fusion; total variation (TV); Algorithms; Brain; Databases, Factual; Image Processing, Computer-Assisted; Least-Squares Analysis; Magnetic Resonance Imaging; Models, Theoretical; Principal Component Analysis; Tomography, X-Ray Computed;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2009.2025006
