Sensor-layer image compression based on the quantized cosine transform

Nikos P. Pitsianis; David J. Brady; Xiaobai Sun

doi:10.1117/12.604921

25 May 2005 Sensor-layer image compression based on the quantized cosine transform

Nikos P. Pitsianis, David J. Brady, Xiaobai Sun

Proceedings Volume 5817, Visual Information Processing XIV; (2005) https://doi.org/10.1117/12.604921
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Nikos P. Pitsianis, David J. Brady, and Xiaobai Sun "Sensor-layer image compression based on the quantized cosine transform", Proc. SPIE 5817, Visual Information Processing XIV, (25 May 2005); https://doi.org/10.1117/12.604921

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