Large image reconstruction based on sparse-banded matrix

Compressed Sensing(CS)is a new technique for simultaneous data sampling and compression. In this paper, aiming at the dimension of measurement matrix is too high for large images to storage, sparse-banded matrix is introduced for reconstructing signals. It reduces independent random variables of measurement matrix. Through processing the large images column by column, the dimension of measurement matrix is greatly reduced. The experimental results show that the image reconstruction algorithm, based on sparse-banded measurement matrix and the approach of column by column, ensures reconstruction quality of images and lower the reconstruction speed.