RESEARCH ARTICLE
Evaluation of a Mathematical Model for Digital Image Enhancement
Hassem Geha 1, Ibrahim Nasseh 2, *, Marcel Noujeim 3
Article Information
Identifiers and Pagination:
Year: 2015Volume: 9
Issue: Suppl 2: M7
First Page: 292
Last Page: 296
Publisher ID: TODENTJ-9-292
DOI: 10.2174/1874210601509010292
Article History:
Received Date: 30/12/2014Revision Received Date: 11/3/2015
Acceptance Date: 25/5/2015
Electronic publication date: 31/7/2015
Collection year: 2015

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
Abstract
Objective : The purpose of this study is to compare the detected number of holes on a stepwedge on images resulting from the application of the 5th degree polynomial model compared to the images resulting from the application of linear enhancement. Material and Methods : A 10-step aluminum step wedge with holes randomly drilled on each step was exposed with three different kVp and five exposure times per kVp on a Schick33® sensor. The images were enhanced by brightness/contrast adjustment, histogram equalization and with the 5th degree polynomial model and compared to the original non-enhanced images by six observers in two separate readings. Results : There was no significant difference between the readers and between the first and second reading. There was a significant three-factor interaction among Method, Exposure time, and kVp in detecting holes. The overall pattern was: “Poly” results in the highest counts, “Original” in the lowest counts, with “B/C” and “Equalized” intermediate. Conclusion : The 5th degree polynomial model showed more holes when compared to the other modalities.