Abstract

Fourier transform holography offers potential benefits for the storage of digital data, including high speed retrieval, reduced alignment constraints, and a high degree of media defect tolerance. Computer generated holography (CGH) provides a means through which holographic storage may be realized by using binary media such as conventional optical disks and tape. The encoding cost for such a scheme as measured by the area overhead η_A, the ratio of the number of hologram pixels to the number of information bits however, is quite high as compared with other methods of error correction encoding. When encoding a binary data word of length N that contains M ones and N – M zeros, we expect that for a fixed encoding cost, the reconstruction quality will decrease as M approaches N. This intuitive notion is verified in simulation. In this paper we will investigate the use of sparse data words (i.e., M « N) for holographic storage. It is found that encoding with a set of sparse words is preferred, from the perspectives of capacity and error tolerance, to other methods of improving reconstruction quality (e.g., increasing the superpixel size in Lee CGH). Sparse data words will also be investigated for other algorithms, such as direct binary search. Simulation results will be compared with optical reconstructions in order to characterize the effects of system imperfections, and other methods that provide some respite from the large capacity cost of CGH will also be presented.

© 1992 Optical Society of America