The use of a Riesz fractional differential-based approach for texture enhancement in image processing

Yu, Q., Liu, F., Turner, I., Burrage, K. and Vegh, V. (2013) The use of a Riesz fractional differential-based approach for texture enhancement in image processing. The ANZIAM Journal, 54 C590-C607. doi:10.0000/anziamj.v54i0.6325

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Author Yu, Q.
Liu, F.
Turner, I.
Burrage, K.
Vegh, V.
Title The use of a Riesz fractional differential-based approach for texture enhancement in image processing
Journal name The ANZIAM Journal   Check publisher's open access policy
ISSN 1446-8735
Publication date 2013
Sub-type Article (original research)
DOI 10.0000/anziamj.v54i0.6325
Open Access Status DOI
Volume 54
Start page C590
End page C607
Total pages 18
Place of publication Cambridge, United Kingdom
Publisher Cambridge University Press
Collection year 2014
Language eng
Formatted abstract
Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.
Keyword Fractional calculus
Texture enhancement
Image processing
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
Centre for Advanced Imaging Publications
 
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Created: Tue, 15 Oct 2013, 15:45:00 EST by Anna Cotroneo on behalf of Centre for Advanced Imaging