A note on the gradient of a multi-image
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
Edge detection in multispectral images
CVGIP: Graphical Models and Image Processing
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Multisensor for Computer Vision
Multisensor for Computer Vision
Subjective tests for image fusion evaluation and objective metric validation
Information Fusion
Intensity gradient based registration and fusion of multi-modal images
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Feature extraction techniques for exploratory visualization of vector-valued imagery
IEEE Transactions on Image Processing
Multispectral image visualization with nonlinear projections
IEEE Transactions on Image Processing
Multispectral image visualization through first-order fusion
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Perceptual Color Correction Through Variational Techniques
IEEE Transactions on Image Processing
From computational attention to image fusion
Pattern Recognition Letters
A study on convex optimization approaches to image fusion
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Multifocus image fusion and denoising: A variational approach
Pattern Recognition Letters
Framelet based pan-sharpening via a variational method
Neurocomputing
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We present a variational model to perform the fusion of an arbitrary number of images while preserving the salient information and enhancing the contrast for visualization. We propose to use the structure tensor to simultaneously describe the geometry of all the inputs. The basic idea is that the fused image should have a structure tensor which approximates the structure tensor obtained from the multiple inputs. At the same time, the fused image should appear `natural' and `sharp' to a human interpreter. We therefore propose to combine the geometry merging of the inputs with perceptual enhancement and intensity correction. This is performed through a minimization functional approach which implicitly takes into account a set of human vision characteristics.