Variational Image Fusion with
Optimal Local Contrast
Mathematical Image Analysis Group, Faculty of Mathematics and Computer Science,
Saarland University, Campus E1.7, 66041 Saarbrücken, Germany
Exemplary applications of our general variational image fusion
technique. Each of the resulting composite images (top) condenses the
most important information from the input stack (bottom).
(Input images are taken from:
In this paper, we present a general variational method for image fusion. In
particular, we combine different images of the same subject to a single
composite that offers optimal exposedness, saturation, and local contrast.
Previous research approaches this task by first precomputing application
specific weights based on the input, and then combining these weights with the
images to the final composite later on.
In contrast, we design our model assumptions directly on the fusion result.
To this end, we formulate the output image as a convex combination of the input
and incorporate concepts from perceptually inspired contrast enhancement such as
a local and nonlinear response. This output-driven approach it the key to the
versatility of our general image fusion model. In this regard, we demonstrate
the performance of our fusion scheme with several applications such as exposure
fusion, multispectral imaging, and decolourisation. For all application
domains, we conduct thorough validations that illustrate the improvements
compared to state-of-the-art approaches that are tailored to the individual
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Variational Image Fusion with Optimal Local Contrast.
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