A Three-Step Approach with Adaptive Additive Magnitude Selection for the Sharpening of Images
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-16
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Aimed to find the additive magnitude automatically and adaptively, we propose a three-step and model-based approach for the sharpening of images in this paper.
In the first pass,a Grey prediction model is applied to find a global maximal additive magnitude so that the condition of oversharpening in images to be sharpened can be avoided.
During the second pass, edge pixels are picked out with our previously proposed edge detection mechanism.
In this pass, a low-pass filter is also applied so that isolated pixels will not be regarded as around an edge.
In the final pass, those pixels detected as around an edge areadjusted adaptively based on the local statistics, and those nonedge pixels are kept unaltered.
Extensive experiments on natural images as well as medical images with subjective and objective evaluations will be given to demonstrate the usefulness of the proposed approach.
American Psychological Association (APA)
Kau, Lih-Jen& Lee, Tien-Lin. 2014. A Three-Step Approach with Adaptive Additive Magnitude Selection for the Sharpening of Images. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1049989
Modern Language Association (MLA)
Kau, Lih-Jen& Lee, Tien-Lin. A Three-Step Approach with Adaptive Additive Magnitude Selection for the Sharpening of Images. The Scientific World Journal No. 2014 (2014), pp.1-15.
https://search.emarefa.net/detail/BIM-1049989
American Medical Association (AMA)
Kau, Lih-Jen& Lee, Tien-Lin. A Three-Step Approach with Adaptive Additive Magnitude Selection for the Sharpening of Images. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1049989
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049989