Maximum segmented-scene spatial entropy thresholding

Chi Kin Leung, F. K. Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

The Segmented-scene Spatial Entropy (SSE) is defined as the amount of information contained in the spatial structure of a segmented scene resulted from segmenting an image. An automatic, non-parametric, unsupervised thresholding algorithm that maximizes the SSE of an image is described, and this algorithm is known as the Maximum Segmented-scene Spatial Entropy (MSSE) thresholding algorithm. It is shown that the MSSE-thresholded image contains the maximum amount of information about the original scene and hence good thresholding results are warranted. Simulation and practical results are presented to illustrate the improvement in performance as compared to some other histogram-based thresholding algorithms.
Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE
Pages963-964
Number of pages2
Publication statusPublished - 1 Dec 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switzerland
Duration: 16 Sep 199619 Sep 1996

Conference

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

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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