Multiscale “Squiral" (Square-Spiral) Image Processing

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

Abstract

In this paper, we present a multiscale “squiral" (square spiral) image processing (SIP) framework. Anefficient spiral addressing scheme is deployed for standard pixel based square images to facilitate fast imageprocessing. A SIP-based convolution technique is developed by simulating the “eye tremor" phenomenon ofthe human visual system. The multiscale SIP operators are constructed by converting existing square imageoperators according to the SIP addressing scheme. The results of edge detection based on three-layer SIPimages and SIP operator at four different scales demonstrate the efficiency of the proposed framework bycomparison with standard 2D convolution.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages8
Publication statusPublished - 26 Aug 2015
EventIrish Machine Vision and Image Processing (IMVIP) - Dublin, Ireland
Duration: 26 Aug 2015 → …

Conference

ConferenceIrish Machine Vision and Image Processing (IMVIP)
Period26/08/15 → …

Fingerprint

Image processing
Convolution
Edge detection
Pixels

Keywords

  • spiral addressing scheme
  • multiscale operator
  • fast image processing
  • edge detection

Cite this

@inproceedings{d38330cd0ebb48e59e29e0c23e8b7599,
title = "Multiscale “Squiral{"} (Square-Spiral) Image Processing",
abstract = "In this paper, we present a multiscale “squiral{"} (square spiral) image processing (SIP) framework. Anefficient spiral addressing scheme is deployed for standard pixel based square images to facilitate fast imageprocessing. A SIP-based convolution technique is developed by simulating the “eye tremor{"} phenomenon ofthe human visual system. The multiscale SIP operators are constructed by converting existing square imageoperators according to the SIP addressing scheme. The results of edge detection based on three-layer SIPimages and SIP operator at four different scales demonstrate the efficiency of the proposed framework bycomparison with standard 2D convolution.",
keywords = "spiral addressing scheme, multiscale operator, fast image processing, edge detection",
author = "Min Jing and SA Coleman and Scotney Bryan and TM McGinnity",
year = "2015",
month = "8",
day = "26",
language = "English",
booktitle = "Unknown Host Publication",

}

Jing, M, Coleman, SA, Bryan, S & McGinnity, TM 2015, Multiscale “Squiral" (Square-Spiral) Image Processing. in Unknown Host Publication. Irish Machine Vision and Image Processing (IMVIP), 26/08/15.

Multiscale “Squiral" (Square-Spiral) Image Processing. / Jing, Min; Coleman, SA; Bryan, Scotney; McGinnity, TM.

Unknown Host Publication. 2015.

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

TY - GEN

T1 - Multiscale “Squiral" (Square-Spiral) Image Processing

AU - Jing, Min

AU - Coleman, SA

AU - Bryan, Scotney

AU - McGinnity, TM

PY - 2015/8/26

Y1 - 2015/8/26

N2 - In this paper, we present a multiscale “squiral" (square spiral) image processing (SIP) framework. Anefficient spiral addressing scheme is deployed for standard pixel based square images to facilitate fast imageprocessing. A SIP-based convolution technique is developed by simulating the “eye tremor" phenomenon ofthe human visual system. The multiscale SIP operators are constructed by converting existing square imageoperators according to the SIP addressing scheme. The results of edge detection based on three-layer SIPimages and SIP operator at four different scales demonstrate the efficiency of the proposed framework bycomparison with standard 2D convolution.

AB - In this paper, we present a multiscale “squiral" (square spiral) image processing (SIP) framework. Anefficient spiral addressing scheme is deployed for standard pixel based square images to facilitate fast imageprocessing. A SIP-based convolution technique is developed by simulating the “eye tremor" phenomenon ofthe human visual system. The multiscale SIP operators are constructed by converting existing square imageoperators according to the SIP addressing scheme. The results of edge detection based on three-layer SIPimages and SIP operator at four different scales demonstrate the efficiency of the proposed framework bycomparison with standard 2D convolution.

KW - spiral addressing scheme

KW - multiscale operator

KW - fast image processing

KW - edge detection

M3 - Conference contribution

BT - Unknown Host Publication

ER -