Automatic detection and extraction of perceptually significant visual features

John Black, Lina Karam

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

1 Scopus citations

Abstract

Perceptual-based algorithms attempt to discriminate between signal components based on their perceptual significance to the human receiver. This paper presents a simple and efficient algorithm for the suppression of non-essential visual features, while retaining those features that are important for the recognition of a scene by a human observer. The first step produces a perceptual mask, which is a spatial perceptual weighting map. This mask assigns perceptual significance to the different areas of the input image, and is used to derive an output image in which the non-essential features of the original image are suppressed. The presented algorithm is motivated by established psychovisual principles related to figure-ground perception and visual illusions, which show that the human visual system is capable of `filling in' missing details when presented with enough visual cues. Very good reconstructed images were obtained despite the reduction in information content. Examples are presented to illustrate the performance of the algorithm.

Original languageEnglish (US)
Title of host publicationConference Record of the Asilomar Conference on Signals, Systems and Computers
EditorsM.P. Farques, R.D. Hippenstiel
PublisherIEEE Comp Soc
Pages315-319
Number of pages5
Volume1
StatePublished - 1998
EventProceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA
Duration: Nov 2 1997Nov 5 1997

Other

OtherProceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2)
CityPacific Grove, CA, USA
Period11/2/9711/5/97

ASJC Scopus subject areas

  • Hardware and Architecture
  • Signal Processing
  • Electrical and Electronic Engineering

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