Mathematical Foundations of Image Interpolation Algorithms
by
Tinku Acharya
Avisere Inc., Kripa Bhawan, Plot - Y20, Block - EP, Sector - V, Salt Lake Electronics Complex, Kolkata - 700094, India.
Coauthors: Ping-Sing Tsai

Image interpolation is an important image processing operation today. It is applied in diverse application areas ranging from computer graphics, image rendering, editing, medical image reconstruction, to online image viewing. Image interpolation techniques are referred in literature by many names, such as image resizing, image re-sampling (up-sampling or down-sampling), digital zooming, image magnification or enhancement, etc. Basically, an image is converted from one resolution (dimension) to another by an image interpolation technique. Image interpolation algorithms in the literature can be grouped in two categories, non-adaptive and adaptive. The key difference between these two categories is that the computation of a non-adaptive image interpolation technique is independent of image contents or features as opposed to an adaptive image interpolation technique. In this paper, we review the progress of both non-adaptive and adaptive image interpolation techniques. We also propose a novel algorithm for image interpolation in this paper. We describe the underlying mathematical foundations of these algorithms and their implementation techniques. We present some experimental results to show the impact of these algorithms in terms of image quality metrics.

Date received: March 26, 2007