A vector coding with a compressive algorithm for natural images

Reiko Osada, Terumasa Aoki, Hiroshi Yasuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a new vector coding with a compressive algorithm for natural images. Here the pixel-value-boundary contours on RGB planes of natural images are expressed by function approximation, and their contour shapes are predicted from similar contours in the decoder side. A vector coding, which represents images by function approximation, not only meets the demands of expansion and reduction but also suits content distribution because of the keeping quality of images even for the repetition of editing. In spite of these merits on vector coding (representation by function approximation based on characteristics of images), the application to natural images has never been studied for its considerably increase of data. To put vector coding for natural images to practical use, we try to compress the data by using characteristics in three-dimensional representation of images.

Original languageEnglish
Title of host publicationICECS 2000 - 7th IEEE International Conference on Electronics, Circuits and Systems
Pages452-455
Number of pages4
Volume1
DOIs
Publication statusPublished - 2000 Dec 1
Externally publishedYes
Event7th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2000 - Jounieh, Lebanon
Duration: 2000 Dec 172000 Dec 20

Other

Other7th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2000
Country/TerritoryLebanon
CityJounieh
Period00/12/1700/12/20

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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