ISSN: 0973-7510

E-ISSN: 2581-690X

Huiyan Jiang1 , Xihe Gao1, Ruijie Feng1 and Hiroshi Fujita2
1Software College, Northeastern University, Shenyang, China.
2Graduate School of Medicine, Gifu University, Yanagido, Gifu, Japan.
J Pure Appl Microbiol. 2013;7(Spl. Edn.: April):389-396
© The Author(s). 2013
Received: 03/03/2013 | Accepted: 14/04/2013 | Published: 30/04/2013

General linear image processing (GLIP) framework, which is based on abstract linear mathematics, opens a new way to the development of image processing techniques by providing specific operations and structures for image representation and processing. This paper presents different models proposed so far for general linear image processing, including the logarithmic image processing (LIP), the general adaptive neighborhood image processing (GANIP), the logarithmic adaptive neighborhood image processing (LANIP)ÿthe parameterized logarithmic image processing (PLIP), the homomorphic logarithmic image processing (HLIP) and the pseudo-logarithmic image processing (Pseudo-LIP). After a description of each approach, we focus on their distinctive theory issues. Several LIP-model based application examples are exposed and discussed in image filtering, edge detection and morphological operation to show the practical advantage of LIP model. This study is helpful for an appropriate use of existing general linear image processing approaches and for systematically designing new approach.


Image processing, Image representation, General linear image processing, Logarithmic image processing

Article Metrics

Article View: 0

Share This Article

© The Author(s) 2013. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License which permits unrestricted use, sharing, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.