Abstract
Image interpolation plays an important role in converting a low resolution image into a high resolution image. This paper provides a comprehensive study of perdurable image interpolation techniques, such as nearest neighbor, bilinear, bicubic, cubic spline, and iterative linear interpolation. The usage of a Lagrange polynomial and a piecewise polynomial gives a better fitting curve for interpolated pixel values. The parameters of interest are the signal-to-noise ratio, peak signal-to-noise ratio, mean square error and processing time. Experiment results are used to analyze the performance of interpolation algorithms. These results help us to choose an appropriate algorithm for better usage.
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