A Total Variation-Based Algorithm for Pixel-Level Image Fusion

Mrityunjay Kumar, Sarat Dass

Research output: Contribution to journalArticlepeer-review

114 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)2137-2143
Number of pages7
JournalIEEE Transactions on Image Processing
Issue number9
Publication statusPublished - Sept 2009


  • Eigenvector
  • forward model
  • image fusion
  • inverse problem
  • pixel-level fusion
  • total variation (TV)


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