CNCS Center for Nonlinear and Complex Systems
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Publications [#280468] of David J. Brady

Papers Published

  1. Pitsianis, NP; Brady, DJ; Sun, X, Sensor-layer image compression based on the quantized cosine transform, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 5817 (November, 2005), pp. 250-257, Orlando, FL, United States, ISSN 0277-786X [Gateway.cgi], [doi]
    (last updated on 2019/11/19)

    We introduce a novel approach for compressive coding at the sensor layer for an integrated imaging system. Compression at the physical layer reduces the measurements-to-pixels ratio and the data volume for storage and transmission, without confounding image estimation or analysis. We introduce a particular compressive coding scheme based on the quantized Cosine transform (QCT) and the corresponding image reconstruction scheme. The QCT is restricted on the ternary set {-1, 0, 1} for economic implementation with a focal plane optical pixel mask. Combined with the reconstruction scheme, the QCT-based coding is shown favorable over existing coding schemes from the coded aperture literature, in terms of both reconstruction quality and photon efficiency.

    Image sensors;Vector quantization;Cosine transforms;Imaging systems;Image quality;