ℓ2 Norm is all Your Need: Infrared-Visible Image Fusion VIA Guided Transformation Minimization

Among the key sub-topics of image fusion, infrared-visible image fusion technology is widely used in modern military and civilian domain. Driven by the data-free and end-to-end advancedness, growing research efforts have been devoted to convert the image fusion task into a norm minimization problem. To simultaneously keep the highlighted thermal information in the infrared image and the clear appearance information in the visible image, we propose a low-complexity fusion algorithm via guided transformation minimization, namely L2GTM. In particular, we formulate the fusion task as a solely `
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norm minimization problem, which enjoys the uniqueness of the optimal solution. To adaptively integrate information from both infrared and visible images, we introduce guided weights to determine the degree of information retention. Experiments on public datasets validate the competitiveness of L2GTM from both the visual quality and objective evaluation perspective.