Nonparametric tests for edge detection in noise

Alan C. Bovik, Thomas S. Huang, David C. Munson

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we describe three statistically motivated techniques for detecting edges in gray-level images. Two similar methods based on linear rank sums are described; specifically, the Wilcoxon and median statistics are implemented in a modified form and are found to perform effectively on both noisy and uncontaminated sample images. A novel approach based on fitting order statistics to the image data is also advanced. Numerous examples are given and computational requirements are examined.

Original languageEnglish (US)
Pages (from-to)209-219
Number of pages11
JournalPattern Recognition
Volume19
Issue number3
DOIs
StatePublished - 1986

Keywords

  • Computer vision
  • Image processing
  • Linear rank sums
  • Nonparametrics
  • Order statistics
  • Statistical edge detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Cite this