A Fast Index Assignment Method for Robust Vector Quantisation of Image Data

Nicola L. C. Talbot, Gavin C. Cawley

Research output: Contribution to conferencePaper


Vector quantisation is a widely used technique in low-bit rate coding of speech and image data, but is highly sensitive to noise in the transmission channel. If the reference vector recalled by a corrupted index differs greatly from the intended reference vector, image quality can be degraded quite dramatically. The index assignment (IA) process attempts to re-order the code book so as to minimise the effects of errors introduced in the transmission channel, by assigning indices with similar binary patterns to similar reference vectors, usually at considerable computational expense. This paper describes a fast, novel index assignment algorithm based on Hall's solution (1970) to the quadratic assignment problem.
Original languageEnglish
Number of pages4
Publication statusPublished - Oct 1997
EventI.E.E.E. International Conference on Image Processing (ICIP-97) - Santa Barbara, United States
Duration: 26 Oct 199729 Oct 1997


ConferenceI.E.E.E. International Conference on Image Processing (ICIP-97)
Country/TerritoryUnited States
CitySanta Barbara

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