Interlinear image interpolation scheme for real time application

Interpolation is a technique for obtaining new unknown data points within the range of discrete known data points and is often used to recover an image from its downsampled version, or to simply perform image expansion. Recently a lot of interpolation algorithms are proposed, but these interpolation algorithms are highly computationally expensive. Hence these algorithms cannot be implemented and used in real time applications. In view of real time applications we have proposed a computationally simple interpolation algorithm. In our proposed algorithm the unknown pixels are categorized into three types depending upon their spatial position. For each type of pixels, distinct methods are used for prediction. The experimental results show that our proposed algorithm excels the conventional interpolation methods in visual effect, and has a lower complexity. Therefore, the algorithm adapts to real-time image resizing.