The image processing domain is experiencing rapid increases in data size and algorithm complexity. These increases in data size and algorithm complexity demand large amounts of computing and storage power. However, modern computer architectures have evolved to be extraordinarily complex, and frequently become a challenge rather than a help for general researchers and educators who work in image processing technologies.
In order to fill the gap between complicated modern architectures and complex applications, and to support the research and education of image processing, the PIs are developing an integrated image processing research environment within a computing Cloud infrastructure. This infrastructure includes: 1) an open image processing computing Cloud to support researchers and students to conduct image processing research, share knowledge and research results, and stimulate education materials among three universities: Prairie View A&M University, University of Houston, and University of Delaware; 2) a high-level domain specific language designed to provide an abstract and productive programming model for image processing applications; 3) a general compiler optimization framework with the capability to tune into image processing applications at various levels starting from high-level representations to low level transformations in the Cloud environment.
