Fast nearest neighbor search for ECVQ and other modified distortion measures

Mary Holland Johnson, Richard Ladner, Eve A. Riskin

Research output: Contribution to conferencePaperpeer-review

13 Scopus citations

Abstract

Many variants of vector quantization offer substantially improved image quality at the cost of additional complexity in encoding. Algorithms for increased speed in nearest neighbor searches for full search VQ using the Euclidean distortion measure have been presented in [1] and [2] with excellent results. We extend these results to any variant of VQ such as Entropy Constrained Vector Quantization (ECVQ) [3], and Bayes-Risk VQ [4], which uses a Lagrangian distortion measure. Additionally we introduce a variation of the existing techniques which provides additional speedup for full search VQ using Euclidean distortion as well as for those VQ's using modified distortion measures.

Original languageEnglish
Pages423-426
Number of pages4
StatePublished - 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: 16 Sep 199619 Sep 1996

Conference

ConferenceProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz
Period16/09/9619/09/96

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