Application of Shape-Independent Orthogonal Transforms for Image Interpolation

Abstract

In the contribution we develop a new method for object-oriented interpolation of images. It is an important tool in image processing, since using interpolation we can considerably decrease amount of data, necessary for image reconstruction. Application of this interpolation enables to down-sample the object separately. The selected object can be processed at the different sampling level. This approach allows object oriented zoom, for example. Moreover, object - oriented approach is a very novel idea that helps to understand the content of image. Method is created from cosine approximation implemented to coding with shape - independent basis functions.