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Targeted filter evolution for improved image reconstruction resolution

Published: 07 July 2007 Publication History

Abstract

Government, commercial, scientific, and defense applications inimage processing often require transmission of large amounts of data across bandwidth-limited channels. Applications require robust transforms simultaneously minimizing bandwidth requirements and image resolution loss. Image processing algorithms take advantage of quantization to provide substantial lossy compression ratios at the expense of resolution. Recent research demonstrates that genetic algorithms evolve filters outperforming standard discrete wavelet transforms in conditions subject to high quantization error. While evolved filters improve overall image quality, wavelet filters typically provide a superior high frequency response, demonstrating improved reconstruction near the edges of objects within an image. This paper presents an algorithm to generate transform filters that optimize edge reconstruction, improving object edge resolution by up to 24%. Such filters provide an increased object resolution over standard wavelets and traditionally evolved filters for varied applications of image processing.

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Cited By

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  • (2020)RETRACTED ARTICLE: Image compression using optimized wavelet filter derived from grey wolf algorithmJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-020-02290-712:6(6677-6688)Online publication date: 1-Aug-2020
  • (2019)Optimization algorithms, an effective tool for the design of digital filters; a reviewJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01431-xOnline publication date: 5-Sep-2019
  • (2010)Image sets for the training of image processing systemsProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830855(2039-2042)Online publication date: 7-Jul-2010
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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 July 2007

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Author Tags

  1. genetic algorithms
  2. image processing
  3. wavelets

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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View all
  • (2020)RETRACTED ARTICLE: Image compression using optimized wavelet filter derived from grey wolf algorithmJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-020-02290-712:6(6677-6688)Online publication date: 1-Aug-2020
  • (2019)Optimization algorithms, an effective tool for the design of digital filters; a reviewJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01431-xOnline publication date: 5-Sep-2019
  • (2010)Image sets for the training of image processing systemsProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830855(2039-2042)Online publication date: 7-Jul-2010
  • (2007)A satellite image set for the evolution of image transforms for defense applicationsProceedings of the 9th annual conference companion on Genetic and evolutionary computation10.1145/1274000.1274031(2901-2906)Online publication date: 7-Jul-2007

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