Nonparametric tests for edge detection in noise

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

doi:10.1016/0031-3203(86)90011-7

Nonparametric tests for edge detection in noise

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

Research output: Contribution to journal › Article › peer-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 language	English (US)
Pages (from-to)	209-219
Number of pages	11
Journal	Pattern Recognition
Volume	19
Issue number	3
DOIs	https://doi.org/10.1016/0031-3203(86)90011-7
State	Published - 1986
Externally published	Yes

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

Online availability

10.1016/0031-3203(86)90011-7

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title = "Nonparametric tests for edge detection in noise",

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.",

keywords = "Computer vision, Image processing, Linear rank sums, Nonparametrics, Order statistics, Statistical edge detection",

author = "Bovik, {Alan C.} and Huang, {Thomas S.} and Munson, {David C.}",

note = "Funding Information: * This work was supported by the Joint Services Electronics Program under contract N000014-79-C-0424.",

year = "1986",

doi = "10.1016/0031-3203(86)90011-7",

language = "English (US)",

volume = "19",

pages = "209--219",

journal = "Pattern Recognition",

issn = "0031-3203",

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TY - JOUR

T1 - Nonparametric tests for edge detection in noise

AU - Bovik, Alan C.

AU - Huang, Thomas S.

AU - Munson, David C.

N1 - Funding Information: * This work was supported by the Joint Services Electronics Program under contract N000014-79-C-0424.

PY - 1986

Y1 - 1986

N2 - 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.

AB - 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.

KW - Computer vision

KW - Image processing

KW - Linear rank sums

KW - Nonparametrics

KW - Order statistics

KW - Statistical edge detection

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VL - 19

SP - 209

EP - 219

JO - Pattern Recognition

JF - Pattern Recognition

IS - 3

ER -

Nonparametric tests for edge detection in noise

Abstract

Keywords

ASJC Scopus subject areas

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