Peripheral Detail-based Edge Preserving Image Interpolation Scheme

Interpolation is a common technique for predicting unknown data points within the range of discrete known data points. In image processing and analysis applications, image interpolation is employed for changing image resolution but also for tasks like image rotation and other transformations. Classical image interpolation algorithms such as nearest neighbour, bilinear and bicubic interpolation are simple and fast. However, due to the high distortion along image details such as edges, the resulting images are often low in quality. In order to reduce these distortions and preserve fine image details, we propose an edge preserving interpolation algorithm in this paper. Our proposed algorithm extracts and recognises the direction of edges in an image. Based on the extracted information about localisation of edges, interpolated pixels are either replicated or predicted from known neighbourhood pixels. Experimental results confirm our approach to give good image quality, outperforming various other interpolation algorithms.