Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Colour Image Retrieval and Object Recognition Using the Multimodal Neighbourhood Signature
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Image Interpolation using Mathematical Morphology
DIAL '06 Proceedings of the Second International Conference on Document Image Analysis for Libraries
Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE's
International Journal of Computer Vision
Example-based single document image super-resolution: a global MAP approach with outlier rejection
Multidimensional Systems and Signal Processing
An image interpolation scheme for repetitive structures
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
New edge-directed interpolation
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
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This paper introduces a Bayesian restoration method for lowresolution images combined with a smoothness prior and a newly proposed adaptive bimodal prior. The bimodal prior is based on the fact that an edge pixel has a colour value that is typically a mixture of the colours of two connected regions, each having a dominant colour distribution. Local adaptation of the parameters of the bimodal prior is made to handle neighbourhoods which have typically more than two dominant colours. The maximum a posteriori estimator is worked out to solve the problem. Experimental results confirm the effectiveness of the proposed bimodal prior and show the visual superiority of our reconstruction scheme to other traditional interpolation and reconstruction methods for images with a strong colour modality like cartoons: noise and compression artefacts are removed very well and our method produces less blur and other annoying artefacts.