Study of Image Interpolation
Amit Prakash Patil, Electronics Engg, Junaid Magdum · 2014
Interpolation is the process of transferring image from one resolution to another without losing image quality. In Image processing field, image interpolation is very important function for doing zooming, enhancement of image, resizing any many more. Conventional image interpolation methods suffer blurring problems in edge regions, so it is hard to produce sharp and clear visual effects. The traditional view of interpolation is to represent an arbitrary continuous function as a discrete sum of weighted and shifted synthesis functions in other words, a mixed convolution equation. An important issue is the choice of adequate synthesis functions that satisfy interpolation properties. Examples of finite-support ones are the square pulse (nearestneighbor interpolation), the hat function (linear interpolation), the cubic Keys' function, and various truncated or windowed versions of the sinc function. On the other hand, splines provide examples of infinite-support interpolation functions that can be realized exactly at a finite, surprisingly small computational cost.