A Complexity Scalable Universal DCT Domain Image Resizing Algorithm

This paper presents a computationally flexible method for producing a mapping from one discrete cosine transform (DCT) domain to another that results in a decoded image that has been arbitrarily resized in the spatial dimension. A notable feature of the proposed mapping is its computational scalability; final image quality can be traded off for lower implementation complexity and a wide range of complexity versus final quality operation points can be realized for each scale factor. Current existing methods often suffer from a lack of flexibility (i.e., work for only one or at most a few resizing factors, have only one or two levels of complexity) or require more operations to achieve similar levels of final image quality. When constructing the mapping, a multiplierless DCT approximation can also be employed, yielding fast implementation with excellent results. The use of the DCT approximation confers several benefits upon the proposed mapping including multiplierless implementation or at most integer operations rather than floating point operations