抽象的

Image Reconstruction Service Using Correlated Compressed Sensing For Privacy Assured Outsourcing in Cloud

P.Arunpriya, S.Rinesh

Large-scale image data sets are being exponentially generated today. Along with such data explosion is the fast growing trend to outsource the image management systems to the cloud for its abundant computing resources and benefits. How to protect the sensitive data while enabling outsourced image services, however, becomes a major concern. Earlier method used compressed sensing for image reconstruction purpose. In that, it supports only typical sparse data acquisition and reconstruction in standard compressed sensing context. However, dense component of image is not considered. In order to provide the correlation of dense and sparse signal of the image we propose a correlated compressed sensing algorithm. This algorithm takes an advantage of the correlation between dense and sparse components of the signal in the recovery procedure at the image decoder side. In this way, we are able to reduce the number of measurements and computation time while obtaining the same accuracy.