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
Generalizing the Nonlocal-means to super-resolution reconstruction
IEEE Transactions on Image Processing
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
Subpixel edge localization and the interpolation of still images
IEEE Transactions on Image Processing
Low-complexity and sampling-aided multi-view video coding at low bitrate
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
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In this paper, we proposed a new edge-directed image interpolation algorithm which can preserve the edge features and natural appearance of images efficiently. In the proposed scheme, we first get a close-form solution of the optimal interpolation coefficients under the sense of minimal mean square error by exploiting autoregressive model (AR) and the geometric duality between the low-resolution and high-resolution images .Then the coefficients of the Nonlocal Edge-directed interpolation (NLEDI) are derived with structure similarity in images, which are solutions of weighted least square equations. The new image interpolation approach preserves spatial coherence of the interpolated images better than the existing methods and it outperforms the other methods in terms of objective and subjective image quality.