1 April 2004 Novel algorithm for image interpolation
Author Affiliations +
Optical Engineering, 43(4), (2004). doi:10.1117/1.1666863
We describe a novel interpolation algorithm to find the optimal image intensity function generating an optimal gray-level estimation of interpolated pixels of digital images. The new approach is based on the proposed image block mapping method and least-square support vector machines (LSSVM) with Gaussian radial basis function (RBF) kernels. With the mapping technique, the interpolation procedure of the LSSVM is actually accomplished in the same input vector space. A number of different scale interpolation experiments are carried out. The experimental results demonstrate that the performance of the proposed algorithm is competitive with many other existing methods, such as cubic, spline, and linear methods. The peak signal-to-noise ratio of the image reconstructed by the proposed algorithm is higher than those obtained by the spline. And the estimated accuracy of the proposed algorithm is similar to that of the cubic algorithm, while the computational requirement is lower than the latter.
Sheng Zheng, Jinwen Tian, Jian Liu, Chengyi Xiong, "Novel algorithm for image interpolation," Optical Engineering 43(4), (1 April 2004). http://dx.doi.org/10.1117/1.1666863

Image processing

Image interpolation

Digital image processing

Reconstruction algorithms


Optical engineering

Vector spaces


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