  This paper observes the application of the Compressive Sensing in
reconstruction of the under-sampled iris images. Iris recognition represents
form of biometric identification whose usage in real applications is growing.
Compressive Sensing represents a novel form of sparse signal acquisition and
recovering when small amount of data is a available. Different sparsity domains
are considered and compared using various number of available image pixels. The
theory is verified on iris images.
