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A Total Variation-Based Algorithm for Pixel-Level Image Fusion
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DOI：10.1109/TIP.2009.2025006.png)
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Abstract
En 中文
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.
Keywords:
Eigenvector
forward model
image fusion
inverse problem
pixel-level fusion
total variation (TV)
Journal
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13.7
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Citations:
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