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A quadratic image interpolation method is stated.
In this article, we presented a novel image interpolation method.
Assuming that a sufficient number of LR frames are available and the proper image registration algorithm is used for compensating the motions existing among the LR frames, multi-frame SR generally outperforms the single image interpolation method.
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For green channel interpolation, any of the existing image interpolation methods can be used and combined with the proposed algorithm.
The experiment results demonstrate that conventional bilinear and bicubic image interpolation methods combined with the proposed strategy can greatly improve the quantitative and qualitative performance for image enlargement.
Conventional image interpolation methods such as the bilinear and bicubic algorithms determine the weights of the reference pixels based on the special distance between the supplementary pixel and the reference pixels.
To determine pixel values of each position in the high-resolution image, interpolation-based methods need to construct a rational interpolation function.
In order to reduce cost and volume, a digital still camera usually utilizes only one sensor and color filter array (CFA) for capturing images, and reconstructs a corresponding full-color image using a color interpolation method.
Third, the 5.0 mm isotropic planning CT and MV-CBCT images were converted again to 1.0 mm isotropic images using the same interpolation method.
This article introduces a new adaptive method for image interpolation.
We present a new method for image interpolation which combines a cell average version of the nonlinear interpolatory technique called PPH (Piecewise Polynomial Harmonic) and subcell resolution techniques.
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