Adding prior knowledge to compressed sensing reconstruction can improve image reconstruction. In this work, two approaches are investigated to improve reconstruction of two-dimensional hyperpolarized (3)He lung ventilation images using prior knowledge. When compared against a standard compressed sensing reconstruction, the proposed methods allowed acquisition of images with higher under-sampling factors and reduction of the blurring effects that increase with higher reduction factors when fixed flip angles are used. These methods incorporate the prior knowledge of polarization decay of hyperpolarized (3)He and the mutual anatomical information from a registered (1)H image acquired in the same breath. Three times accelerated two-dimensional images reconstructed with compressed sensing and prior knowledge gave lower root-mean square error, than images reconstructed without introduction of any prior information. When introducing the polarization decay as prior knowledge, a significant improvement was achieved in the lung region, the root mean square value decreased by 45% and from the whole image by 36%. When introducing the mutual anatomical information as prior knowledge, the root mean square decreased by 21% over the lung region and by 15% over the whole image.