High Quality Alias Free Image Rotation

This paper presents new algorithms for the rotation of images. The primary design criteria for these algorithms is very high quality. Common methods for image rotation, including convolutional and separable approaches, are examined and shown to exhibit significant high frequency aliasing problems. A new resampling filter design methodology is presented which minimizes the problem for conventional convolution-based image rotation. The paper also presents a new separable image rotation algorithm which exhibits improved performance in term of reduction in artifacts and an efficient O(N 2 logN ) running time. 1. Introduction Rotation is a very basic image processing operation. Many applications, such as radiology and photographic analysis, require very high quality image rotation. The goal of the work presented here is efficient image rotation of the highest possible quality. An image is defined, for the purpose of this paper, as a discrete sampling of a continuous two-dimensional funct..