Linked Life Data

19933015

Source:http://linkedlifedata.com/resource/pubmed/id/19933015

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-1-19
pubmed:abstractText
In this paper, we intend to implement a class of fractional differential masks with high-precision. Thanks to two commonly used definitions of fractional differential for what are known as GrUmwald-Letnikov and Riemann-Liouville, we propose six fractional differential masks and present the structures and parameters of each mask respectively on the direction of negative x-coordinate, positive x-coordinate, negative y-coordinate, positive y-coordinate, left downward diagonal, left upward diagonal, right downward diagonal, and right upward diagonal. Moreover, by theoretical and experimental analyzing, we demonstrate the second is the best performance fractional differential mask of the proposed six ones. Finally, we discuss further the capability of multiscale fractional differential masks for texture enhancement. Experiments show that, for rich-grained digital image, the capability of nonlinearly enhancing complex texture details in smooth area by fractional differential-based approach appears obvious better than by traditional intergral-based algorithms.
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:month
Feb
pubmed:issn
1941-0042
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
19
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
491-511
pubmed:year
2010
pubmed:articleTitle
Fractional differential mask: a fractional differential-based approach for multiscale texture enhancement.
pubmed:affiliation
School of Computer Science andTechnology, Sichuan University, 610065 Chengdu, China. puyifei_007@163.com
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't