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Proceedings Paper

Sensor-layer image compression based on the quantized cosine transform
Author(s): Nikos P. Pitsianis; David J. Brady; Xiaobai Sun
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Paper 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.

Paper Details

Date Published: 25 May 2005
PDF: 8 pages
Proc. SPIE 5817, Visual Information Processing XIV, (25 May 2005); doi: 10.1117/12.604921
Show Author Affiliations
Nikos P. Pitsianis, Duke Univ. (United States)
David J. Brady, Duke Univ. (United States)
Xiaobai Sun, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 5817:
Visual Information Processing XIV
Zia-ur Rahman; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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