  Recent advances in computing such as the massively parallel GPUs (Graphical
Processing Units),coupled with the need to store and deliver large quantities
of digital data especially images, has brought a number of challenges for
Computer Scientists, the research community and other stakeholders. These
challenges, such as prohibitively large costs to manipulate the digital data
amongst others, have been the focus of the research community in recent years
and has led to the investigation of image compression techniques that can
achieve excellent results. One such technique is the Discrete Cosine Transform,
which helps separate an image into parts of differing frequencies and has the
advantage of excellent energy-compaction.
  This paper investigates the use of the Compute Unified Device Architecture
(CUDA) programming model to implement the DCT based Cordic based Loeffler
algorithm for efficient image compression. The computational efficiency is
analyzed and evaluated under both the CPU and GPU. The PSNR (Peak Signal to
Noise Ratio) is used to evaluate image reconstruction quality in this paper.
The results are presented and discussed.
