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We present an overview of our research effort on volume holographic digital data storage. Innovations, developments, and new insights gained in the design and operation of working storage platforms, novel optical components and techniques, data coding and signal processing algorithms, systems tradeoffs, materials testing and tradeoffs, and photon-gated storage materials are summarized.

QBlC* lets users find pictorial information in large image and video databases based on color, shape, texture, and sketches. QBIC technology is part of several I B M products. 'To run an interacnve query, vult the QBIC Web sewer at http //imwqbic almaden ibm COW Semantic versus nonsemantic information icture yourself as a fashion designer needing images of fabrics with a particular mixture of colors, a museum cataloger looking P for artifacts of a particular shape and textured pattern, or a movie producer needing a video clip of a red car-like object moving from right to left with the camera zooming. How do you find these images? Even though today's technology enables us to acquire, manipulate, transmit, and store vast on-line image and video collections, the search methodologies used to find pictorial information are still limited due to difficult research problems (see "Semantic versus nonsemantic" sidebar). Typically, these methodologies depend on file IDS, keywords, or text associated with the images. And, although powerful, they don't allow queries based directly on the visual properties of the images, are dependent on the particular vocabulary used, and don't provide queries for images similar to a given image. Research on ways to extend and improve query methods for image databases is widespread, and results have been presented in workshops, conferences,'.* and surveys. We have developed the QBIC (Query by Image Content) system to explore content-based retrieval methods. QBIC allows queries on large image and video databases based on example images, user-constructed sketches and drawings, selected color and texture patterns,

We describe a digital holographic storage system for the study of noise sources and the evaluation of modulation and error-correction codes. A precision zoom lens and Fourier transform optics provide pixel-to-pixel matching between any input spatial light modulator and output CCD array over magnifications from 0.8 to 3. Holograms are angle multiplexed in LiNbO(3):Fe by use of the 90 degrees geometry, and reconstructions are detected with a 60-frame/s CCD camera. Modulation codes developed on this platform permit image transmission down to signal levels of ~2000 photons per ON camera pixel, at raw bit-error rates (BER's) of better than 10(-5). Using an 8-12-pixel modulation code, we have stored and retrieved 1200 holograms (each with 45,600 user bits) without error, for a raw BER of <2x10(-8).

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The problem of scalar and vector quantization in conjunction with a noisy binary symmetric channel is considered. The issue is the assignment of the shortest possible distinct binary sequences to quantization levels or vectors so as to minimize the mean squared error caused by channel errors. By formulating the assignment as a matrix (or vector in the scalar case) and showing that the mean squared error due to channel errors is determined by the projections of its columns onto the eigenspaces of the multidimensional channel transition matrix, a class of source/quantizer pairs is identi ed for which the optimal index assignment has a simple and natural form. Among other things, this provides a simpler and more accessible proof of the result of Crimmins et al. that the natural binary code is an optimal index assignment for the uniform scalar quantizer and uniform source. It also provides a potentially useful approach to further developments in sourcechannel coding. Index terms: source-channel coding, natural binary code, vector quantization.