Title :
Rateless lossy compression via the extremes
Author :
No, A. ; Weissman, T.
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
fDate :
Sept. 30 2014-Oct. 3 2014
Abstract :
We begin by presenting a simple lossy compressor operating at near-zero rate: The encoder merely describes the indices of the few maximal source components, while the decoder´s reconstruction is a natural estimate of the source components based on this information. This scheme turns out to be near-optimal for the memoryless Gaussian source in the sense of achieving the zero-rate slope of its distortion-rate function. Motivated by this finding, we then propose a scheme comprising of iterating the above lossy compressor on an appropriately transformed version of the difference between the source and its reconstruction from the previous iteration. The proposed scheme achieves the rate distortion function of the Gaussian memoryless source (under squared error distortion) when employed on any finite-variance ergodic source. It further possesses desirable properties we respectively refer to as infinitesimal successive refinability, ratelessness, and complete separability. Its storage and computation requirements are of order no more than n2/logβn per source symbol for β > 0 at both the encoder and decoder. Though the details of its derivation, construction, and analysis differ considerably, we discuss similarities between the proposed scheme and the recently introduced SPARC of Venkataramanan et al.
Keywords :
Gaussian processes; encoding; matrix algebra; Gaussian memoryless source; distortion-rate function; extreme value theory; finite-variance ergodic source; order statistics; rateless lossy compression; spherical distribution; squared error distortion; uniform random orthogonal matrix; zero-rate slope; Decoding; Indexes; Rate distortion theory; Rate-distortion; Source coding; Vectors; Complete separability; extreme value theory; infinitesimal successive refinability; order statistics; rate distortion code; rateless code; spherical distribution; uniform random orthogonal matrix;
Conference_Titel :
Communication, Control, and Computing (Allerton), 2014 52nd Annual Allerton Conference on
Conference_Location :
Monticello, IL
DOI :
10.1109/ALLERTON.2014.7028440