Performance analysis of the effects of non-adaptive image scaling on image edges

Abstract

changing the dimensions of an image by increasing or decreasing is called image scaling or image resizing. There are many techniques aim at achieving this process with minimal distortions and good quality. Non-adaptive techniques such as nearest neighbor interpolation, bilinear interpolation, bicubic interpolation, Lanczos interpolation, and B-spline interpolation are good examples of achieving a reasonably good quality when the fine details of an image and the edges are not of great concern. The process of image resizing results in unequal proportions of image details and edges. Adaptive image scaling produce images with reasonably good quality at the cost of processing time. The non-adaptive interpolation is preferred in real time applications due to its fast processing time and reasonably good quality. In this paper, the non-adaptive interpolation techniques will be introduced and compared. New methods for evaluating the performance of these techniques will be introduced. The ratio of the pixels of image edges to the total image pixels will be calculated.