Block-level parallel processing for scaling evenly divisible frames

Multiresolution video streaming and medical image processing require image scaling. The paper shows how image scaling can be accelerated with a new coarse-grained parallel processing method. The method is based on evenly divisible image sizes, which is, in practice, the case in most video and image standards. The image is divided into slices and all the slices are scaled in parallel. The complexity of the method is evaluated with two parallel architectures while considering memory consumption and data throughput. Several scaling functions can be handled with these generic architectures, including bilinear, bicubic, Lagrange, Gaussian and sinc interpolations. Parallelism can be adjusted independently of the complexity of the computational units.