Local Scale Control for Edge Detection and Blur Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction and representation of 3D objects with radial basis functions
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Warped distance for space-variant linear image interpolation
IEEE Transactions on Image Processing
Regularity-preserving image interpolation
IEEE Transactions on Image Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Adaptively quadratic (AQua) image interpolation
IEEE Transactions on Image Processing
An edge-guided image interpolation algorithm via directional filtering and data fusion
IEEE Transactions on Image Processing
A New Orientation-Adaptive Interpolation Method
IEEE Transactions on Image Processing
The Error-Amended Sharp Edge (EASE) Scheme for Image Zooming
IEEE Transactions on Image Processing
Image Interpolation by Adaptive 2-D Autoregressive Modeling and Soft-Decision Estimation
IEEE Transactions on Image Processing
Markov Random Field Model-Based Edge-Directed Image Interpolation
IEEE Transactions on Image Processing
Subpixel edge localization and the interpolation of still images
IEEE Transactions on Image Processing
Edge-directed image interpolation using color gradient information
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
A Framework for Moving Least Squares Method with Total Variation Minimizing Regularization
Journal of Mathematical Imaging and Vision
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In this paper, we present a novel edge-directed upsampling method based on radial basis function (RBF) interpolation. In order to remove artifacts such as blurred edges or blocking effects, we suggest a nonlinear method capable of taking edge information into account. The resampling evaluation is determined according to the edge orientation. The proposed scheme is as simple to implement as linear methods but it demonstrates improved visual quality by preserving the edge features better than the classical linear interpolation methods. The algorithm is compared with some well-known linear schemes as well as recently developed nonlinear schemes. The resulting images demonstrate the new algorithm's ability to magnify an image while preserving the edge features.