Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
New edge-directed interpolation
IEEE Transactions on Image Processing
An edge-guided image interpolation algorithm via directional filtering and data fusion
IEEE Transactions on Image Processing
Image Interpolation by Adaptive 2-D Autoregressive Modeling and Soft-Decision Estimation
IEEE Transactions on Image Processing
Spatial-temporal motion compensation based video super resolution
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Sparse representation based face image super-resolution
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Depth image enlargement using an evolutionary approach
Image Communication
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This paper presents a novel non-local iterative back-projection (NLIBP) algorithm for image enlargement. The iterative back-projection (IBP) technique iteratively reconstructs a high resolution (HR) image from its blurred and downsampled low resolution (LR) counterpart. However, the conventional IBP methods often produce many "jaggy" and "ringing" artifacts because the reconstruction errors are back projected into the reconstructed image isotropically and locally. In natural images, usually there exist many non-local redundancies which can be exploited to improve the image reconstruction quality. Therefore, we propose to incorporate adaptively the non-local information into the IBP process so that the reconstruction errors can be reduced. Experimental results demonstrated that the proposed NLBP can reconstruct faithfully the HR images with sharp edges and texture structures. It outperforms the state-of-the-art methods in both PSNR and visual perception.