Block based compressive sensing algorithm using Eigen vectors for image compression

The image compression is widely used throughout the multimedia applications and presently many standard techniques are already available, however the in many situation (like after encryption, highly textured etc.) the data compression with the stated techniques are not sufficient, for such cases that relatively new approach called Compressive Sensing can provide a better results as recent research shows. The Compressive Sensing is a concepts primarily used for reduction in reduction in number of observation required for reconstructing the data from linear acquisition system. It fundamentally states that a linear system with N number of equations can be approximated by M equation (M <; N), if system follows sparsely condition. The paper utilizes the same concept for image compression, however the reduction in approximated system equation is performed by calculating the Eigen vectors. The application of Eigen value and vector not only simplifies the process but also provides efficient reconstruction with high compression. The simulation results also verifies the superiority proposed algorithm over previous algorithms by considerable margin.