Sub-pixel Image Magnification Using Adaptive Linear Interpolation
Hoon Yoo
Abstract
Hoon Yoo
Abstract
We propose an adaptive linear interpolation locating sub-pixels. We utilize a pixel-based parameter in the conventional linear interpolation. To optimally obtain the parameter, we propose a generic interpolation structure including a low pass filter and minimum mean square error. We also propose a simple version of the generic interpolation method, which obtain a closed-form solution. Simulation results show that the proposed method is superior to the state-of-the-art methods such as warped distance linear interpolation and shifted linear interpolation, as well as the conventional method such as the linear interpolation and the cubic convolution interpolation in terms of the subjective and objective image quality.
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We propose an adaptive linear interpolation locating sub-pixels. We utilize a pixel-based parameter in the conventional linear interpolation. To optimally obtain the parameter, we propose a generic interpolation structure including a low pass filter and minimum mean square error. We also propose a simple version of the generic interpolation method, which obtain a closed-form solution. Simulation results show that the proposed method is superior to the state-of-the-art methods such as warped distance linear interpolation and shifted linear interpolation, as well as the conventional method such as the linear interpolation and the cubic convolution interpolation in terms of the subjective and objective image quality.
Key concepts: Stairstep interpolation, Linear interpolation, Interpolation (computer graphics), Demosaicing, Image scaling, Nearest-neighbor interpolation, Trilinear interpolation, Bilinear interpolation